Triple
T30949756
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harrisburg, Texas |
E788502
|
entity |
| Predicate | wasBurnedIn |
P102908
|
FINISHED |
| Object | April 1836 |
—
|
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: April 1836 | Statement: [Harrisburg, Texas, wasBurnedIn, April 1836]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasBurnedIn Context triple: [Harrisburg, Texas, wasBurnedIn, April 1836]
-
A.
burnedDuring
Indicates that one event, object, or process was actively burning or being consumed by fire during the time span of another specified event or interval.
-
B.
burnedAt
Indicates that something was subjected to burning at a specific time or in a specific event.
-
C.
hasBurnUnit
Indicates that one entity (typically a medical facility) includes or is equipped with a specialized unit dedicated to the treatment and care of burn patients.
-
D.
burned
Indicates that one entity caused another entity to be damaged or consumed by fire or intense heat.
-
E.
burnedDownIn
chosen
Indicates that a structure or object was destroyed by fire during a particular event or incident.
- 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_69f224c180f88190ad177372ee02b7e2 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f697eabb048190bc01a830f14942c6 |
completed | May 3, 2026, 12:33 a.m. |
| PD | Predicate disambiguation | batch_69f69664142c8190bc695501056b0236 |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 29, 2026, 8:53 p.m.