Triple
T16127157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miraculous Medal |
E391300
|
entity |
| Predicate | firstStruck |
P121575
|
FINISHED |
| Object | 1832 |
—
|
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: 1832 | Statement: [Miraculous Medal, firstStruck, 1832]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstStruck Context triple: [Miraculous Medal, firstStruck, 1832]
-
A.
first
Indicates that one entity precedes all others in an ordered sequence or ranking.
-
B.
firstFight
Indicates that the referenced event is the initial instance in which the involved entities engaged in a fight or combat with each other.
-
C.
firstShotsFiredBy
Indicates which party or entity initiated a conflict or incident by discharging the first shots.
-
D.
firstLeg
Indicates that one entity represents the initial segment or starting portion of a multi-part journey, sequence, or process involving another entity.
-
E.
firstSuccessfulImpactBy
Indicates that one entity is the earliest or initial successful impactor upon another entity in a given context or sequence of events.
- F. None of above. chosen
Provenance (4 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_69d87f1bb0988190b490d273dbf3fd03 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e20205bed48190a6930439738da191 |
completed | April 17, 2026, 9:48 a.m. |
| PD | Predicate disambiguation | batch_69e1828518c48190a8ef3aaa46a1f639 |
completed | April 17, 2026, 12:44 a.m. |
| PDg | Predicate description generation | batch_69e183b9d3f08190953ada68f4272996 |
completed | April 17, 2026, 12:50 a.m. |
Created at: April 10, 2026, 5 a.m.