Triple
T37910024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Primrose Path |
E945659
|
entity |
| Predicate | hasJoelMcCreaRole |
P189607
|
FINISHED |
| Object | Ed Wallace |
—
|
NE NERFINISHED |
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: Ed Wallace | Statement: [Primrose Path, hasJoelMcCreaRole, Ed Wallace]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasJoelMcCreaRole Context triple: [Primrose Path, hasJoelMcCreaRole, Ed Wallace]
-
A.
hasGlennFordRole
Indicates that an entity has a role played by the actor Glenn Ford.
-
B.
hasWilliamHoldenRole
Indicates that an entity has a role played by the actor William Holden.
-
C.
hasJoanFontaineRole
Indicates that an entity has a role played by Joan Fontaine in a film, television, or theatrical production.
-
D.
hasRitaHayworthRole
Indicates that an entity has a role or character associated with Rita Hayworth, such as portraying her or a role closely linked to her.
-
E.
hasFredMacMurrayRole
Indicates that an entity has a role or character portrayed by Fred MacMurray in a work (such as a film or television production).
- 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_69f76ef20bb0819088b5b6ceecb0b8fc |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbc36ce1f88190a7fa1656b714e107 |
completed | May 6, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69fbbd166a488190b1bf9316b0790801 |
completed | May 6, 2026, 10:13 p.m. |
| PDg | Predicate description generation | batch_69fbc36bcac48190a726b40442c094d1 |
completed | May 6, 2026, 10:40 p.m. |
Created at: May 3, 2026, 4:20 p.m.