Triple
T2618067
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bombardment of Fort Sumter |
E58936
|
entity |
| Predicate | timeOfFirstShot |
P13395
|
FINISHED |
| Object | 1861-04-12T04:30 |
—
|
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: 1861-04-12T04:30 | Statement: [Bombardment of Fort Sumter, timeOfFirstShot, 1861-04-12T04:30]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeOfFirstShot Context triple: [Bombardment of Fort Sumter, timeOfFirstShot, 1861-04-12T04:30]
-
A.
firstShotsFiredAt
chosen
Indicates the location or time at which the initial gunshots or opening fire in an incident occurred.
-
B.
firstShotsFiredBy
Indicates which party or entity initiated a conflict or incident by discharging the first shots.
-
C.
firstShotsFiredOn
Indicates that the referenced event or entity marks the initial occurrence of shots being fired on a specified date, time, or occasion.
-
D.
numberOfShotsFired
Indicates the total count of shots that were discharged in the described event or action.
-
E.
OneOClockGunFirstFired
Indicates that the One O'Clock Gun was fired for the first time.
- 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_69ab4ac444dc819099614e534dd6021f |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abdaca581881908fe8d3d820f839b7 |
completed | March 7, 2026, 7:59 a.m. |
| PD | Predicate disambiguation | batch_69abd80f48888190afdf7e3e042157d0 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:50 p.m.