Triple
T2200937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lorraine Broughton |
E50485
|
entity |
| Predicate | missionInFilm |
P68
|
FINISHED |
| Object | recover a list of undercover agents |
—
|
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: recover a list of undercover agents | Statement: [Lorraine Broughton, missionInFilm, recover a list of undercover agents]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: missionInFilm Context triple: [Lorraine Broughton, missionInFilm, recover a list of undercover agents]
-
A.
mission
chosen
Indicates that an entity is assigned or engaged in a specific task, operation, or purpose-directed undertaking.
-
B.
missionName
Indicates the designated title or label assigned to a specific mission or operation.
-
C.
missionField
Indicates a relationship where an entity’s work, activity, or purpose is directed toward a particular area, domain, or target context as its mission focus.
-
D.
missionFocus
Indicates that an entity’s primary attention, effort, or resources are directed toward a particular mission, goal, or objective.
-
E.
missionProfile
Indicates the specific set of objectives, conditions, and operational parameters that define how a mission is planned, conducted, and evaluated.
- F. None of above.
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_69a88b044ab48190add007487680f009 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abbfa06bb4819092d7021358846e5f |
completed | March 7, 2026, 6:03 a.m. |
| PD | Predicate disambiguation | batch_69abbda706f4819094de73e1d1d1f539 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:46 p.m.