Triple
T9814993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lacey Pemberton |
E238378
|
entity |
| Predicate | hasFriend |
P8712
|
FINISHED |
| Object |
Radar
Radar is a character known as one of Lacey Pemberton’s close friends in John Green’s novel "Paper Towns."
|
E823583
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Radar | Statement: [Lacey Pemberton, hasFriend, Radar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Radar Context triple: [Lacey Pemberton, hasFriend, Radar]
-
A.
Radar
Radar is the nickname of American professional golfer Michael Reid, known for his accuracy and steady play on the PGA Tour.
-
B.
Radar Pictures
Radar Pictures is an American film and television production company known for developing and producing a wide range of feature films and series across genres.
-
C.
Liana radar
Liana radar is an airborne early warning and control radar system used on the Russian Beriev A-50 aircraft to detect, track, and manage aerial and surface targets.
-
D.
Erieye radar
The Erieye radar is a Swedish airborne early warning and control (AEW&C) radar system known for its active electronically scanned array (AESA) technology and long-range surveillance capabilities.
-
E.
Stinger
Stinger is the anthropomorphic green hornet mascot of the NHL’s Columbus Blue Jackets, known for his energetic presence at games and team events.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Radar Triple: [Lacey Pemberton, hasFriend, Radar]
Generated description
Radar is a character known as one of Lacey Pemberton’s close friends in John Green’s novel "Paper Towns."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Radar Target entity description: Radar is a character known as one of Lacey Pemberton’s close friends in John Green’s novel "Paper Towns."
-
A.
Radar
Radar is the nickname of American professional golfer Michael Reid, known for his accuracy and steady play on the PGA Tour.
-
B.
Radar Pictures
Radar Pictures is an American film and television production company known for developing and producing a wide range of feature films and series across genres.
-
C.
Liana radar
Liana radar is an airborne early warning and control radar system used on the Russian Beriev A-50 aircraft to detect, track, and manage aerial and surface targets.
-
D.
Erieye radar
The Erieye radar is a Swedish airborne early warning and control (AEW&C) radar system known for its active electronically scanned array (AESA) technology and long-range surveillance capabilities.
-
E.
Stinger
Stinger is the anthropomorphic green hornet mascot of the NHL’s Columbus Blue Jackets, known for his energetic presence at games and team events.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca84dfde1481909f47c286d715f892 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb2f19660819083e3f15780352052 |
completed | April 2, 2026, 12:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1cc67db68819093217c9a74e72fbf |
completed | April 5, 2026, 2:43 a.m. |
| NEDg | Description generation | batch_69d1ccf59c68819082b4aa37e06d2aaf |
completed | April 5, 2026, 2:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1d0d945d48190b56b7fd2ce568a13 |
completed | April 5, 2026, 3:02 a.m. |
Created at: March 30, 2026, 8:30 p.m.