Triple
T3556129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ilchester |
E75222
|
entity |
| Predicate | wasRomanTown |
P50574
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Ilchester, wasRomanTown, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasRomanTown Context triple: [Ilchester, wasRomanTown, true]
-
A.
nearbyRomanTown
Indicates that one location is geographically close to a town that existed during the Roman period.
-
B.
RomanTribe
Indicates a relationship where an entity belongs to, is classified within, or is associated with a specific Roman tribe.
-
C.
romanRoad
Indicates that one location is connected to another by a road constructed or used during the Roman period.
-
D.
wasCitadelOf
Indicates that a place previously served as the main fortified stronghold or central defensive structure for another entity.
-
E.
RomanRepresentative
Indicates that one entity serves as an official representative or agent of the Roman state, authority, or interests in relation to another entity.
- 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_69ad85d45090819086f34fb85d850a1e |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc057cc788190a6c4f3781f43abce |
completed | March 8, 2026, 6:30 p.m. |
| PD | Predicate disambiguation | batch_69adb83270ac819083967db0570167d2 |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adba25c66c81909a05a97327828c41 |
completed | March 8, 2026, 6:04 p.m. |
Created at: March 8, 2026, 3:20 p.m.