Triple
T29353307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Main Hall |
E744369
|
entity |
| Predicate | isOftenLocatedNear |
P115314
|
FINISHED |
| Object | mainReception |
—
|
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: mainReception | Statement: [Main Hall, isOftenLocatedNear, mainReception]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isOftenLocatedNear Context triple: [Main Hall, isOftenLocatedNear, mainReception]
-
A.
isOftenLocatedAround
Indicates that one entity is frequently found in the vicinity of, or surrounding, another entity.
-
B.
oftenLocatedNear
chosen
Indicates that one entity is frequently found in close physical proximity to another entity.
-
C.
oftenLocatedAs
Indicates that one entity is frequently found or situated in the same place as another entity.
-
D.
oftenLocatedAt
Indicates that an entity is frequently or commonly found at, or associated with being in, a particular location.
-
E.
locatedInOrAdjacentTo
Indicates that one entity is either situated within the boundaries of another entity or directly next to it, sharing a common border or edge.
- 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_69f0a79a2d748190bc30abd469298b37 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f66d7765208190b87b1cc6d96a151c |
completed | May 2, 2026, 9:32 p.m. |
| PD | Predicate disambiguation | batch_69f66abfdaf08190a55f14c70be6fd4d |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 28, 2026, 2:08 p.m.