Triple
T16589047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naseeruddin Shah |
E403033
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Paar |
E728378
|
NE FINISHED |
How this triple was built (2 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: Paar | Statement: [Naseeruddin Shah, notableWork, Paar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paar Context triple: [Naseeruddin Shah, notableWork, Paar]
-
A.
Paar
Paar is a surname most notably associated with American television host and comedian Jack Paar, a pioneering figure of late-night talk shows.
-
B.
Paar
chosen
"Paar" is a critically acclaimed Indian film directed by Goutam Ghose, known for its stark portrayal of social injustice and rural hardship.
-
C.
Paar
Paar is a river in Bavaria, Germany, known for flowing through several towns and rural landscapes before joining the Danube.
-
D.
Pareja
Pareja is a Spanish surname borne by various notable individuals, including Colombian former footballer and coach Óscar Pareja.
-
E.
Çifteler
Çifteler is a town and district in central Turkey known for its agricultural activities and location within Eskişehir Province in the Central Anatolia region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d88387363c8190a97a0c942130de97 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3599e79288190b6bcdb6fe4a2d1fa |
completed | April 18, 2026, 10:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a007599dcd4819089bbd0569b3d9a12 |
completed | May 10, 2026, 12:10 p.m. |
Created at: April 10, 2026, 5:16 a.m.