Triple
T148383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Court |
E3377
|
entity |
| Predicate | hasSpatialRole |
P4755
|
FINISHED |
| Object | focalPointOfComposition |
—
|
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: focalPointOfComposition | Statement: [Great Court, hasSpatialRole, focalPointOfComposition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpatialRole Context triple: [Great Court, hasSpatialRole, focalPointOfComposition]
-
A.
isAssociatedWith
Indicates that there exists a connection, relationship, or involvement between two entities without specifying its exact nature.
-
B.
temporalRelation
Indicates a relationship that specifies how two events or states are positioned relative to each other in time (e.g., before, after, or overlapping).
-
C.
refersToRole
Indicates that one entity designates, mentions, or points to another entity specifically in its capacity as a role or position.
-
D.
role
Indicates the function, position, or responsibility that one entity holds in relation to another within a given context.
-
E.
embodiedBy
chosen
Indicates that an abstract concept, role, or function is physically or concretely realized in a specific entity.
- 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a257ecb6f48190992c4c8ca908a81c |
completed | Feb. 28, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69a256599db08190a7b000b381d32ec4 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.