Triple
T33219395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anand Bakshi |
E850377
|
entity |
| Predicate | numberOfFilmSongsWritten |
P203968
|
FINISHED |
| Object | over 4000 |
—
|
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: over 4000 | Statement: [Anand Bakshi, numberOfFilmSongsWritten, over 4000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfFilmSongsWritten Context triple: [Anand Bakshi, numberOfFilmSongsWritten, over 4000]
-
A.
hasWrittenSongsFor
Indicates that one entity has composed songs specifically intended to be performed, recorded, or used by another entity.
-
B.
notableSongWrittenFor
Indicates that a particular song was specifically written for a given person, group, work, event, or purpose.
-
C.
hasWrittenLyricsFor
Indicates that one entity is the lyricist who has created the words for a song or musical work performed or associated with another entity.
-
D.
containsSongWrittenBy
Indicates that an entity (such as an album, playlist, or collection) includes at least one song that was written by a specified creator or songwriter.
-
E.
numberOfFilmScores
Indicates the total count of film scores that an entity has composed or is credited with.
- 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_69f3496083dc8190b229bb6932dc548b |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a0301289dbc8190a4372958d3451171 |
completed | May 12, 2026, 10:30 a.m. |
| PD | Predicate disambiguation | batch_6a0300d4185c8190a383d5da3659bc4f |
completed | May 12, 2026, 10:28 a.m. |
| PDg | Predicate description generation | batch_6a030127f5ec8190add78cf709b57611 |
completed | May 12, 2026, 10:30 a.m. |
Created at: May 1, 2026, 1:30 a.m.