Triple
T12600062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greenwich Pensioners |
E300832
|
entity |
| Predicate | typeOfPensioner |
P12837
|
FINISHED |
| Object | in‑pensioner |
—
|
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: in‑pensioner | Statement: [Greenwich Pensioners, typeOfPensioner, in‑pensioner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfPensioner Context triple: [Greenwich Pensioners, typeOfPensioner, in‑pensioner]
-
A.
receivesPensionFrom
Indicates that one entity is the source or provider of a pension that another entity receives.
-
B.
pensionNature
chosen
Indicates the type or characteristics of a pension, such as its form, conditions, or classification within a benefits or retirement scheme.
-
C.
pensionIssue
Indicates that an entity is involved in the granting, receiving, managing, or disputing of a pension or retirement-benefit payment.
-
D.
retirementPattern
Indicates the typical way or schedule in which an entity withdraws from active service, work, or use.
-
E.
pensionAmount
Indicates the specific monetary value of a pension that is assigned to or received by an entity.
- F. None of above.
Provenance (3 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_69d7bdea2ca881908f379526c13b1145 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9559458dc8190bc4d6e697e99d70e |
completed | April 10, 2026, 7:55 p.m. |
| PD | Predicate disambiguation | batch_69d9541894fc8190a0c3706a414279f0 |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 9, 2026, 5:09 p.m.