Triple
T21202839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sahir Ludhianvi |
E522499
|
entity |
| Predicate | wroteLyricsForFilm |
P92748
|
FINISHED |
| Object |
Didi
Didi is a 1959 Hindi-language Indian film best known for its popular music and emotionally driven storytelling.
|
E1471968
|
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: Didi | Statement: [Sahir Ludhianvi, wroteLyricsForFilm, Didi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Didi Context triple: [Sahir Ludhianvi, wroteLyricsForFilm, Didi]
-
A.
Didi
Didi was a legendary Brazilian attacking midfielder, renowned for his playmaking brilliance and key role in Brazil’s World Cup victories in 1958 and 1962.
-
B.
Didi Petet
Didi Petet was a prominent Indonesian actor and comedian best known for his roles in popular films and television series from the 1980s and 1990s.
-
C.
Didi Dache
Didi Dache was a pioneering Chinese taxi-hailing mobile app that later became part of the ride-hailing giant Didi Chuxing.
-
D.
Dida
Dida is a Brazilian former professional goalkeeper best known for his time at AC Milan, where he was regarded as one of the world’s top keepers in the early 2000s.
-
E.
Dida
"Dida" is a song best known from Joan Baez’s repertoire, often associated with her 1970s folk and singer-songwriter work.
- 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: Didi Triple: [Sahir Ludhianvi, wroteLyricsForFilm, Didi]
Generated description
Didi is a 1959 Hindi-language Indian film best known for its popular music and emotionally driven storytelling.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Didi Target entity description: Didi is a 1959 Hindi-language Indian film best known for its popular music and emotionally driven storytelling.
-
A.
Didi
Didi was a legendary Brazilian attacking midfielder, renowned for his playmaking brilliance and key role in Brazil’s World Cup victories in 1958 and 1962.
-
B.
Didi Petet
Didi Petet was a prominent Indonesian actor and comedian best known for his roles in popular films and television series from the 1980s and 1990s.
-
C.
Didi Dache
Didi Dache was a pioneering Chinese taxi-hailing mobile app that later became part of the ride-hailing giant Didi Chuxing.
-
D.
Dida
Dida is a Brazilian former professional goalkeeper best known for his time at AC Milan, where he was regarded as one of the world’s top keepers in the early 2000s.
-
E.
Dida
"Dida" is a song best known from Joan Baez’s repertoire, often associated with her 1970s folk and singer-songwriter work.
- 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_69e0b5112d8881909510b2dcdc93106d |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e73432a2b88190a89e636626d40c9b |
completed | April 21, 2026, 8:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a097ed0fc988190b112058f5bb03515 |
completed | May 17, 2026, 8:39 a.m. |
| NEDg | Description generation | batch_6a09807f39188190adaba95201b15d49 |
completed | May 17, 2026, 8:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0981288c4c8190bc9ecf6073be5ab3 |
completed | May 17, 2026, 8:49 a.m. |
Created at: April 16, 2026, 3:19 p.m.