Triple
T206218
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jennifer Hudson |
E4614
|
entity |
| Predicate | film |
P9968
|
FINISHED |
| Object | Respect |
E26328
|
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: Respect | Statement: [Jennifer Hudson, film, Respect]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Respect Context triple: [Jennifer Hudson, film, Respect]
-
A.
Respect
chosen
Respect is a 2021 biographical drama film depicting the life and career of legendary soul singer Aretha Franklin, starring Jennifer Hudson in the lead role.
-
B.
Grace
Grace is the central Christian concept of God’s unmerited favor and loving initiative toward humanity, enabling salvation and spiritual transformation.
-
C.
Truth and Service
Truth and Service is the English motto of Howard University, encapsulating its commitment to academic integrity and community uplift.
-
D.
Truth and Service
Truth and Service is the guiding motto of North Carolina Central University, emphasizing a commitment to integrity and community engagement.
-
E.
Valor
Valor is a concept or quality associated with courage and bravery in the context of warfare and heroic action.
- 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_69a25737567c81908f9c505300239181 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a260c178ac819085eb94ccaf64b780 |
completed | Feb. 28, 2026, 3:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a32f29799c8190a445a231006bf436 |
completed | Feb. 28, 2026, 6:08 p.m. |
Created at: Feb. 28, 2026, 2:51 a.m.