Triple
T9359819
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | History of Salem, Massachusetts |
E225248
|
entity |
| Predicate | GreatSalemFireEffect |
P52514
|
FINISHED |
| Object | destruction of large commercial and residential areas |
—
|
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: destruction of large commercial and residential areas | Statement: [History of Salem, Massachusetts, GreatSalemFireEffect, destruction of large commercial and residential areas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: GreatSalemFireEffect Context triple: [History of Salem, Massachusetts, GreatSalemFireEffect, destruction of large commercial and residential areas]
-
A.
firstBuildingDestroyedByFire
Indicates that the first building in a given context was destroyed as a result of a fire.
-
B.
fireEffect
chosen
Indicates that one entity produces, causes, or is associated with a fire-related impact or consequence on another entity.
-
C.
fireIncidentRelated
Indicates that there is a connection or association between a specific fire incident and another entity, event, or record.
-
D.
notableFire
Indicates that a significant or historically important fire event is associated with the subject.
-
E.
significantBuildingFire
Indicates a relationship where a building is involved in a fire event of notable size, intensity, or impact.
- 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_69ca842bdd648190904131d58620d448 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd4ff2ca9081908ccc88651640ed84 |
completed | April 1, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69cc7a68ab9481909f97cb70764697cc |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:42 p.m.