Triple
T8503863
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Javed Akhtar |
E201285
|
entity |
| Predicate | numberOfFilmfareAwardsForBestLyricist |
P82866
|
FINISHED |
| Object | multiple |
—
|
LITERAL 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: multiple | Statement: [Javed Akhtar, numberOfFilmfareAwardsForBestLyricist, multiple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfFilmfareAwardsForBestLyricist Context triple: [Javed Akhtar, numberOfFilmfareAwardsForBestLyricist, multiple]
-
A.
lyricist
Indicates that one entity is the writer of the words (lyrics) for a musical work associated with another entity.
-
B.
notableLyricist
Indicates that the subject is a lyricist who is particularly distinguished or well-known for their work.
-
C.
writerOfMusicAndLyrics
Indicates that a person is the creator of both the musical composition and the song lyrics for a work.
-
D.
hasMusicDirector
Indicates that an entity (such as a film, show, or production) is associated with a specific person who served as its music director.
-
E.
mostNominationsRecipient
Indicates that the subject is the entity that has received the highest number of nominations within a given context or set.
- F. None of above. chosen
Provenance (4 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_69ca831fe47c8190b5c57b456d2aefa0 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe59d67d081908155a43b9b463fe3 |
completed | March 31, 2026, 3:17 p.m. |
| PD | Predicate disambiguation | batch_69cbd10cfd208190a519049fad32c508 |
completed | March 31, 2026, 1:50 p.m. |
| PDg | Predicate description generation | batch_69cbe12dd0b88190a38ec4d15dcc870b |
completed | March 31, 2026, 2:58 p.m. |
Created at: March 30, 2026, 6:14 p.m.