Triple
T14238942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brigadier Lethbridge-Stewart |
E352956
|
entity |
| Predicate | recurringEra |
P113348
|
FINISHED |
| Object | UNIT era of Doctor Who |
—
|
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: UNIT era of Doctor Who | Statement: [Brigadier Lethbridge-Stewart, recurringEra, UNIT era of Doctor Who]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recurringEra Context triple: [Brigadier Lethbridge-Stewart, recurringEra, UNIT era of Doctor Who]
-
A.
endedEra
Indicates that one entity brought about or marked the conclusion of a particular era associated with another entity.
-
B.
historicalEraRecreated
Indicates that a past historical era has been reconstructed or simulated, typically for representation, study, or experiential purposes.
-
C.
partOfEra
Indicates that one entity exists as a temporal segment or component within the duration or scope of a larger historical era.
-
D.
followsEra
Indicates that one time period or era comes directly after another in chronological order.
-
E.
recurringDuring
Indicates that an event or state happens repeatedly within the time span or context defined by another event or interval.
- 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_69d8278adc7c8190a9218d69bce3c4e6 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de62432fb48190b153805b85c4f2d2 |
completed | April 14, 2026, 3:50 p.m. |
| PD | Predicate disambiguation | batch_69de05bf069c8190b69f00f00f5eb126 |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de239bd0f48190ada38c0261e0ef3c |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 10, 2026, 1:08 a.m.