Triple
T1013942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | On Her Majesty's Secret Service |
E21887
|
entity |
| Predicate | featuresAlias |
P23264
|
FINISHED |
| Object | 007 |
—
|
LITERAL 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: 007 | Statement: [On Her Majesty's Secret Service, featuresAlias, 007]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresAlias Context triple: [On Her Majesty's Secret Service, featuresAlias, 007]
-
A.
featuresCross
Indicates that one feature or element intersects or passes across another in space or structure.
-
B.
featuresGroup
Indicates that an entity includes or is associated with a specific group as one of its features or components.
-
C.
featuresAngel
Indicates that something includes or prominently presents an angel as a central element or subject.
-
D.
featuresSupporter
Indicates that one entity serves as a supporter, advocate, or promoter of another entity or its cause.
-
E.
featuresText
Indicates that an entity includes or presents a specific piece of text as one of its characteristics or contents.
- 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_69a493c68e24819080ed0ee8bcfd5ce0 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b7be907c8190b5c6ea89257755a7 |
completed | March 1, 2026, 10:03 p.m. |
| PD | Predicate disambiguation | batch_69a4b72207c08190a3dbb2aa7acbbc71 |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b7bd3d50819091e6f1d2ffe4c7ee |
completed | March 1, 2026, 10:03 p.m. |
Created at: March 1, 2026, 7:41 p.m.