Triple
T14034442
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Littoria |
E337673
|
entity |
| Predicate | laterProvinceName |
P112571
|
FINISHED |
| Object | province of Latina |
—
|
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: province of Latina | Statement: [Littoria, laterProvinceName, province of Latina]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterProvinceName Context triple: [Littoria, laterProvinceName, province of Latina]
-
A.
laterProvince
Indicates that one administrative region or province succeeds another in time, coming into existence or effect after the other.
-
B.
formerProvince
Indicates that an entity was previously a province of another entity but no longer holds that administrative status.
-
C.
previousProvince
Indicates that one province was the immediately preceding administrative region of another in a temporal or historical sequence.
-
D.
formerNameOfProvince
Indicates that one name was previously used as the official name of a province before being replaced by another name.
-
E.
hadProvince
Indicates that a governing entity possessed administrative control or jurisdiction over a specific province.
- 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_69d81c664e48819088cbd8f433aeffe5 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2fac71188190a586049405f1071e |
completed | April 14, 2026, 12:14 p.m. |
| PD | Predicate disambiguation | batch_69de05ab36b48190920efb1869bdb1fe |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de2398856c81908bed6070e4ca6ab1 |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 9, 2026, 10:20 p.m.