Triple
T22404228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jefferson Hills |
E553840
|
entity |
| Predicate | hasPark |
P105
|
FINISHED |
| Object |
Tepe Park
Tepe Park is a local public park and recreational green space located in Jefferson Hills, Pennsylvania.
|
E1533638
|
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: Tepe Park | Statement: [Jefferson Hills, hasPark, Tepe Park]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tepe Park Context triple: [Jefferson Hills, hasPark, Tepe Park]
-
A.
Fayaz Tepe
Fayaz Tepe is an ancient Buddhist monastic complex near Termez in southern Uzbekistan, notable for its well-preserved murals and role in the spread of Buddhism along the Silk Road.
-
B.
Anıttepe
Anıttepe is a central hill and neighborhood in Ankara, Turkey, best known as the site of Anıtkabir, the mausoleum of Mustafa Kemal Atatürk.
-
C.
Masatepe
Masatepe is a town in Nicaragua known for its traditional culture, crafts, and as the birthplace of prominent writer and politician Sergio Ramírez.
-
D.
Dzhambaz Tepe
Dzhambaz Tepe is one of the historic hills in Plovdiv, Bulgaria, known as part of the ancient urban landscape of the city of Philippopolis.
-
E.
Hayrettin Tepe
Hayrettin Tepe is a Turkish entrepreneur best known for establishing and leading the Tepe Group business conglomerate.
- 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: Tepe Park Triple: [Jefferson Hills, hasPark, Tepe Park]
Generated description
Tepe Park is a local public park and recreational green space located in Jefferson Hills, Pennsylvania.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tepe Park Target entity description: Tepe Park is a local public park and recreational green space located in Jefferson Hills, Pennsylvania.
-
A.
Fayaz Tepe
Fayaz Tepe is an ancient Buddhist monastic complex near Termez in southern Uzbekistan, notable for its well-preserved murals and role in the spread of Buddhism along the Silk Road.
-
B.
Anıttepe
Anıttepe is a central hill and neighborhood in Ankara, Turkey, best known as the site of Anıtkabir, the mausoleum of Mustafa Kemal Atatürk.
-
C.
Masatepe
Masatepe is a town in Nicaragua known for its traditional culture, crafts, and as the birthplace of prominent writer and politician Sergio Ramírez.
-
D.
Dzhambaz Tepe
Dzhambaz Tepe is one of the historic hills in Plovdiv, Bulgaria, known as part of the ancient urban landscape of the city of Philippopolis.
-
E.
Hayrettin Tepe
Hayrettin Tepe is a Turkish entrepreneur best known for establishing and leading the Tepe Group business conglomerate.
- 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_69e11e4da7048190b4387d422a9a0de5 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f158b6762c8190991fc14c5ca8e609 |
completed | April 29, 2026, 1:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0ae9cfabe081908d6a001bcfe5372c |
completed | May 18, 2026, 10:28 a.m. |
| NEDg | Description generation | batch_6a0aea5eef848190893c8b7f6066092d |
completed | May 18, 2026, 10:30 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0aeaf55efc81909438a39cbfd5e723 |
completed | May 18, 2026, 10:33 a.m. |
Created at: April 16, 2026, 8:46 p.m.