Triple
T7568690
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hartford Civic Center |
E179183
|
entity |
| Predicate | demolishedPartially |
P23714
|
FINISHED |
| Object | late 1970s |
—
|
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 1970s | Statement: [Hartford Civic Center, demolishedPartially, late 1970s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: demolishedPartially Context triple: [Hartford Civic Center, demolishedPartially, late 1970s]
-
A.
partiallyDestroyed
chosen
Indicates that an entity has been damaged or ruined to a significant extent but not completely destroyed.
-
B.
demolishedAsPartOf
Indicates that one entity was demolished as a component or consequence of a larger demolition event or project involving another entity.
-
C.
partlyDismantledBy
Indicates that an entity has been only partially taken apart, removed, or deconstructed by another agent or process.
-
D.
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.
-
E.
demolishedWith
Indicates that one entity was destroyed or torn down using another specified tool, method, or agent.
- 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_69c69f316e50819081a271c85c06f918 |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f91d9bfc8190af6f5f8211c3dda2 |
completed | March 27, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69c6f4de77048190b8769e717fdcf8e7 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:51 p.m.