Triple
T5752922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Damsels in Distress |
E126893
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Heather |
E225544
|
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: Heather | Statement: [Damsels in Distress, mainCharacter, Heather]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Heather Context triple: [Damsels in Distress, mainCharacter, Heather]
-
A.
Heather
chosen
Heather is a feminine given name of English origin, derived from the flowering shrub commonly found on moorlands.
-
B.
The Meadows
The Meadows is a central shopping complex in Chelmsford, England, featuring a range of retail stores, eateries, and services.
-
C.
The Meadows
The Meadows is a large public park and green space in central Edinburgh, popular for recreation, sports, and community events.
-
D.
The Meadow
The Meadow is a large open green space within Delaware Park in Buffalo, New York, commonly used for recreation, events, and outdoor gatherings.
-
E.
Wildwood
Wildwood is a popular seaside resort city on the Jersey Shore known for its expansive beaches, lively boardwalk, and classic Doo Wop–style motels.
- 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_69c00832aedc81909899801b141fa3b4 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c029032ba08190ae4062d74ab271ee |
completed | March 22, 2026, 5:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c07e3e71988190a938a6d175023028 |
completed | March 22, 2026, 11:41 p.m. |
Created at: March 22, 2026, 3:48 p.m.