Triple
T37049149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Henry (Jerry) |
E917001
|
entity |
| Predicate | rescueInvolved |
P134021
|
FINISHED |
| Object | mob action to free him from custody |
—
|
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: mob action to free him from custody | Statement: [William Henry (Jerry), rescueInvolved, mob action to free him from custody]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rescueInvolved Context triple: [William Henry (Jerry), rescueInvolved, mob action to free him from custody]
-
A.
involvedRescue
chosen
Indicates that an entity participated in or contributed to a rescue operation or act of saving someone or something from danger.
-
B.
involvedInAccident
Indicates that an entity participated in, was affected by, or was otherwise a party to a specific accident or collision event.
-
C.
constantInvolved
Indicates that a constant participates in or is directly involved in the specified relation, operation, or context.
-
D.
rightInvolved
Indicates that an entity is involved in or associated with a legal or formal right held, exercised, or affected in a given context.
-
E.
fortInvolved
Indicates that a fort is involved or participates in a particular event, action, or relationship between entities.
- 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_69f76e94d0308190a3f06890e133c88e |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb34e5576881909394355c8ec6ddd2 |
completed | May 6, 2026, 12:32 p.m. |
| PD | Predicate disambiguation | batch_69fb2f6171e88190bf1e0ee6a644b6a9 |
completed | May 6, 2026, 12:09 p.m. |
Created at: May 3, 2026, 4:14 p.m.