Triple
T15632307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trees Lounge |
E375844
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Tommy Basilio
Tommy Basilio is the aimless, hard-drinking ex-mechanic whose personal and emotional struggles drive the narrative of the indie film "Trees Lounge."
|
E1168009
|
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: Tommy Basilio | Statement: [Trees Lounge, mainCharacter, Tommy Basilio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tommy Basilio Context triple: [Trees Lounge, mainCharacter, Tommy Basilio]
-
A.
Tommy Barban
Tommy Barban is a daring and enigmatic soldier of fortune who plays a pivotal role in F. Scott Fitzgerald’s novel "Tender Is the Night."
-
B.
Tommy Lipuma
Tommy LiPuma was an influential American record producer and music industry executive known for his work with major pop and jazz artists across several decades.
-
C.
Tommy Vig
Tommy Vig is a Hungarian-American jazz vibraphonist, composer, and bandleader known for his work in both European and American jazz scenes.
-
D.
Tommy Nova
Tommy Nova is a music producer known for his work on hip-hop projects such as the track "Shaolin vs. Wu-Tang."
-
E.
Tommy Brue
Tommy Brue is a middle-aged British banker entangled in espionage and moral ambiguity in John le Carré’s spy novel "A Most Wanted Man."
- 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: Tommy Basilio Triple: [Trees Lounge, mainCharacter, Tommy Basilio]
Generated description
Tommy Basilio is the aimless, hard-drinking ex-mechanic whose personal and emotional struggles drive the narrative of the indie film "Trees Lounge."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tommy Basilio Target entity description: Tommy Basilio is the aimless, hard-drinking ex-mechanic whose personal and emotional struggles drive the narrative of the indie film "Trees Lounge."
-
A.
Tommy Barban
Tommy Barban is a daring and enigmatic soldier of fortune who plays a pivotal role in F. Scott Fitzgerald’s novel "Tender Is the Night."
-
B.
Tommy Lipuma
Tommy LiPuma was an influential American record producer and music industry executive known for his work with major pop and jazz artists across several decades.
-
C.
Tommy Vig
Tommy Vig is a Hungarian-American jazz vibraphonist, composer, and bandleader known for his work in both European and American jazz scenes.
-
D.
Tommy Nova
Tommy Nova is a music producer known for his work on hip-hop projects such as the track "Shaolin vs. Wu-Tang."
-
E.
Tommy Brue
Tommy Brue is a middle-aged British banker entangled in espionage and moral ambiguity in John le Carré’s spy novel "A Most Wanted Man."
- 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_69d85cd035a48190b73d5579ab73969a |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04eb7338881909f3c430bb73f91d1 |
completed | April 16, 2026, 2:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff5f472b648190b7cd532a1b16373e |
completed | May 9, 2026, 4:22 p.m. |
| NEDg | Description generation | batch_69ff606f627081909e6ea230f30c917b |
completed | May 9, 2026, 4:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff6136a8c88190a83ad9232a338082 |
completed | May 9, 2026, 4:30 p.m. |
Created at: April 10, 2026, 4:14 a.m.