Triple
T19449745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hagibor complex in Prague |
E486582
|
entity |
| Predicate | locatedInArea |
P40
|
FINISHED |
| Object |
Hagibor
Hagibor is a district in Prague known for its residential developments and modern urban infrastructure.
|
E1376365
|
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: Hagibor | Statement: [Hagibor complex in Prague, locatedInArea, Hagibor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hagibor Context triple: [Hagibor complex in Prague, locatedInArea, Hagibor]
-
A.
Hakutaka
Hakutaka is a high-speed train service operating on Japan’s Hokuriku Shinkansen line, connecting Tokyo with cities along the Sea of Japan coast.
-
B.
Taketoyo
Taketoyo is a coastal town in central Japan known for its industrial facilities and location within Aichi Prefecture.
-
C.
Honjo
Honjo is a historic district in Tokyo known for its traditional shitamachi atmosphere and close ties to the Sumida River area.
-
D.
Hobokan
Hobokan is an alternative name or spelling for the place or entity known as Hobuck.
-
E.
Shigemori
Shigemori is a Japanese given name most notably borne by Taira no Shigemori, a prominent 12th-century samurai and statesman of the Taira clan.
- 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: Hagibor Triple: [Hagibor complex in Prague, locatedInArea, Hagibor]
Generated description
Hagibor is a district in Prague known for its residential developments and modern urban infrastructure.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hagibor Target entity description: Hagibor is a district in Prague known for its residential developments and modern urban infrastructure.
-
A.
Hakutaka
Hakutaka is a high-speed train service operating on Japan’s Hokuriku Shinkansen line, connecting Tokyo with cities along the Sea of Japan coast.
-
B.
Taketoyo
Taketoyo is a coastal town in central Japan known for its industrial facilities and location within Aichi Prefecture.
-
C.
Honjo
Honjo is a historic district in Tokyo known for its traditional shitamachi atmosphere and close ties to the Sumida River area.
-
D.
Hobokan
Hobokan is an alternative name or spelling for the place or entity known as Hobuck.
-
E.
Shigemori
Shigemori is a Japanese given name most notably borne by Taira no Shigemori, a prominent 12th-century samurai and statesman of the Taira clan.
- 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_69d8e8d7ad488190a3373045029b0f3b |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6338caeb48190aeb1d511996984e3 |
completed | April 20, 2026, 2:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a073b3175248190817aedbfd95927dc |
completed | May 15, 2026, 3:26 p.m. |
| NEDg | Description generation | batch_6a073be7e28c8190999dacec37a2f3b4 |
completed | May 15, 2026, 3:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a073c9461d08190a2b89ebd16e66a58 |
completed | May 15, 2026, 3:32 p.m. |
Created at: April 10, 2026, 1:38 p.m.