Triple
T22003451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Elizabeth Weir |
E543388
|
entity |
| Predicate | hasRankInStory |
P121402
|
FINISHED |
| Object | Civilian authority |
—
|
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: Civilian authority | Statement: [Dr. Elizabeth Weir, hasRankInStory, Civilian authority]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRankInStory Context triple: [Dr. Elizabeth Weir, hasRankInStory, Civilian authority]
-
A.
hasLeaderInStory
Indicates that one entity serves as the leader of another entity within the context of a specific story or narrative.
-
B.
hasAwardInStory
Indicates that an entity is depicted within a narrative or story as having received a particular award.
-
C.
hasRankInFiction
chosen
Indicates that a fictional character or entity holds a specific rank, title, or hierarchical position within a fictional context or universe.
-
D.
rankInBackstory
Indicates the position or status an entity holds within another entity’s narrative background or origin story.
-
E.
hasAllyInStory
Indicates that one entity is portrayed as an ally or supportive partner of another entity within the context of a specific story or narrative.
- 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_69e11e2c814c8190837d072789000486 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1276cab5c8190ac1236fde7e0394a |
completed | April 28, 2026, 9:32 p.m. |
| PD | Predicate disambiguation | batch_69e6f62dc9d88190ae387f145f9528de |
completed | April 21, 2026, 3:59 a.m. |
Created at: April 16, 2026, 8:20 p.m.