Triple
T4294014
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King of the French |
E99663
|
entity |
| Predicate | firstUseAsTitleDate |
P55282
|
FINISHED |
| Object | 1791 |
—
|
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: 1791 | Statement: [King of the French, firstUseAsTitleDate, 1791]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstUseAsTitleDate Context triple: [King of the French, firstUseAsTitleDate, 1791]
-
A.
firstUsedOn
Indicates the date, time, or context in which something was initially applied, activated, or put into use on a particular object or entity.
-
B.
firstTitleSince
Indicates that an entity has achieved a particular title for the first time since a specified earlier point, event, or prior title occurrence.
-
C.
firstUsedBy
Indicates that something was initially utilized, applied, or employed by a particular entity before any others.
-
D.
firstUsedFor
Indicates that one entity was the earliest or original thing for which another entity was used or applied.
-
E.
firstIntroductionDate
Indicates the date on which an entity was first introduced or presented for the first time.
- 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_69b3455175088190aa79c6e03b86647e |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35083f87c8190a3d3b323e76ab575 |
completed | March 12, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_69b347fe55a88190b77bab0c0f38e1aa |
completed | March 12, 2026, 11:10 p.m. |
| PDg | Predicate description generation | batch_69b34e0606488190baadf469a1afc3c2 |
completed | March 12, 2026, 11:36 p.m. |
Created at: March 12, 2026, 11:08 p.m.