Triple
T763988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaiju |
E16133
|
entity |
| Predicate | typicalRole |
P18942
|
FINISHED |
| Object | city-destroying monster |
—
|
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: city-destroying monster | Statement: [Kaiju, typicalRole, city-destroying monster]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalRole Context triple: [Kaiju, typicalRole, city-destroying monster]
-
A.
roleInText
Indicates that an entity participates in a text with a specific function or capacity (e.g., author, editor, character).
-
B.
roleInvolves
Indicates that a particular role includes or requires participation in a specified activity, responsibility, or function.
-
C.
typeOfRole
Indicates that one entity specifies the kind or category of role that another entity holds or performs.
-
D.
roleInDialogue
Indicates that an entity participates in a dialogue with a specific conversational role (e.g., speaker, listener, moderator) relative to other participants.
-
E.
depictsPersonRole
Indicates that an image or representation shows a person in a specific role, function, or capacity.
- 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_69a493684ee48190bd43b7c78da4aec8 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a69c8c448190a036a04fd8fdd2c2 |
completed | March 1, 2026, 8:50 p.m. |
| PD | Predicate disambiguation | batch_69a4a506106081909ef97a679ff00a5a |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a5a35c68819082429755c046e9a7 |
completed | March 1, 2026, 8:46 p.m. |
Created at: March 1, 2026, 7:37 p.m.