Triple
T1088402
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anjou |
E24104
|
entity |
| Predicate | dateAbsorbedApprox |
P23345
|
FINISHED |
| Object | 15th century |
—
|
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: 15th century | Statement: [Anjou, dateAbsorbedApprox, 15th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dateAbsorbedApprox Context triple: [Anjou, dateAbsorbedApprox, 15th century]
-
A.
acquisitionDate
Indicates the date on which one entity formally acquires or takes ownership of another entity.
-
B.
dateApproximate
Indicates that the associated date is not exact but estimated or approximate rather than precisely known.
-
C.
inceptionDate
Indicates the date on which an entity, event, or relationship was first created, established, or began to exist.
-
D.
dateGranted
Indicates the specific date on which a right, status, or permission was formally conferred or approved.
-
E.
dateOfConversion
Indicates the specific date on which an entity changed status, form, or affiliation (e.g., religious, legal, or organizational conversion).
- 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_69a49404428c819092dcc9632f5f7b8b |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b97d85708190a1630256648aa4a2 |
completed | March 1, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69a4b741b0cc8190be001a16a81f6d9e |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b7bd3d50819091e6f1d2ffe4c7ee |
completed | March 1, 2026, 10:03 p.m. |
Created at: March 1, 2026, 7:42 p.m.