Triple
T12503851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Assault on Fort Wagner |
E298894
|
entity |
| Predicate | relatedWork |
P37
|
FINISHED |
| Object | film "Glory" |
E987390
|
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: film "Glory" | Statement: [Assault on Fort Wagner, relatedWork, film "Glory"]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: film "Glory" Context triple: [Assault on Fort Wagner, relatedWork, film "Glory"]
-
A.
film "Glory"
chosen
"Glory" is a 1989 American war drama film that tells the story of one of the first African American regiments in the Union Army during the American Civil War, highlighting their bravery and struggle against racism.
-
B.
Glory
"Glory" is an Academy Award–winning civil rights anthem by John Legend and Common, written for the 2014 film *Selma* and celebrated for its powerful commentary on racial justice.
-
C.
Glory
Glory is the airline callsign used by UNI Air, a Taiwanese regional carrier.
-
D.
Glory
Glory is a feminine given name most notably associated with American professional basketball player Glory Johnson.
-
E.
Glory
"Glory" is a song performed by American singer Celia.
- 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_69d6ada4cd388190ae3bbf83ff87057a |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94dfcea188190a929db1aabe1a286 |
completed | April 10, 2026, 7:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f65570401c819084f9db2eff5fdf3e |
completed | May 2, 2026, 7:50 p.m. |
Created at: April 8, 2026, 9:57 p.m.