Triple
T37798973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Addison Corday |
E942314
|
entity |
| Predicate | trapInvolved |
P189229
|
FINISHED |
| Object | razor box trap |
—
|
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: razor box trap | Statement: [Addison Corday, trapInvolved, razor box trap]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trapInvolved Context triple: [Addison Corday, trapInvolved, razor box trap]
-
A.
constantInvolved
Indicates that a constant participates in or is directly involved in the specified relation, operation, or context.
-
B.
fortInvolved
Indicates that a fort is involved or participates in a particular event, action, or relationship between entities.
-
C.
passInvolved
Indicates that an entity is involved in a passing action, either as the passer, receiver, or otherwise participating party.
-
D.
frontInvolved
Indicates that an entity is directly involved in or associated with the front (e.g., front line, front-facing part, or leading edge) of another entity or situation.
-
E.
trap
Indicates that an entity captures, confines, or ensnares another entity, typically preventing its escape or movement.
- 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_69f76ee6f1f4819091e2cf9c9e6aee19 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbb9e8108c8190ae1c7940b1677e95 |
completed | May 6, 2026, 10 p.m. |
| PD | Predicate disambiguation | batch_69fbb141605c8190b9c27d70352522db |
completed | May 6, 2026, 9:23 p.m. |
| PDg | Predicate description generation | batch_69fbb9e69b7481909beaf8264d87c5e5 |
completed | May 6, 2026, 10 p.m. |
Created at: May 3, 2026, 4:19 p.m.