Triple
T12118262
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fort McIntosh |
E288621
|
entity |
| Predicate | demolishedOrAbandoned |
P92154
|
FINISHED |
| Object | late 18th century |
—
|
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: late 18th century | Statement: [Fort McIntosh, demolishedOrAbandoned, late 18th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: demolishedOrAbandoned Context triple: [Fort McIntosh, demolishedOrAbandoned, late 18th century]
-
A.
demolishedOrDestroyed
chosen
Indicates that one entity has caused another entity to be torn down, ruined, or rendered unusable, typically through deliberate demolition or destructive force.
-
B.
demolished
Indicates that one entity completely destroyed or razed another entity, typically a structure or object, so that it no longer exists in its previous form.
-
C.
demolishedWith
Indicates that one entity was destroyed or torn down using another specified tool, method, or agent.
-
D.
demolishedAfter
Indicates that one entity was demolished at a point in time later than the demolition of another entity.
-
E.
demolishedOrAbsorbed
Indicates that one entity has ceased to exist independently because it was either physically destroyed or organizationally absorbed into another 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_69d6ab4a5c448190a110d1273314b21a |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9164ada5081908676bd9e5947268a |
completed | April 10, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69d9150497408190921334d21503375a |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:49 p.m.