Triple
T16877391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Ivan Morrison |
E421333
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Gloria |
E865314
|
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: Gloria | Statement: [George Ivan Morrison, notableWork, Gloria]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gloria Context triple: [George Ivan Morrison, notableWork, Gloria]
-
A.
Gloria
Gloria is a 1980 American crime drama film written and directed by John Cassavetes, starring Gena Rowlands as a tough ex-mobster’s girlfriend protecting a young boy from gangsters.
-
B.
Gloria
Gloria is a fictional character featured in Green Day’s song “¡Viva La Gloria!” from their rock opera album 21st Century Breakdown.
-
C.
Gloria
chosen
"Gloria" is a 1982 dance-pop hit song by American singer Laura Branigan that became one of her signature tracks and a major international success.
-
D.
Gloria
"Gloria" is a work associated with Northern Irish actor Colin Morgan, known for his roles in television, film, and theatre.
-
E.
Gloria
Gloria is a specific horse, likely recognized as an individual member of a larger group or stable of horses.
- 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_69d889d470fc8190b4aec199636c0c56 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3b7f704a081909921d00b3c470472 |
completed | April 18, 2026, 4:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00c2b4abd08190841c5bb0b0eaa177 |
completed | May 10, 2026, 5:39 p.m. |
Created at: April 10, 2026, 5:29 a.m.