Triple
T32710721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Panther platform |
E836396
|
entity |
| Predicate | firstModelYearInService |
P187816
|
FINISHED |
| Object | 1979 |
—
|
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: 1979 | Statement: [Panther platform, firstModelYearInService, 1979]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstModelYearInService Context triple: [Panther platform, firstModelYearInService, 1979]
-
A.
inServiceStartYear
chosen
Indicates the year in which an entity first entered into active service or operation.
-
B.
firstArrivalYear
Indicates the calendar year in which an entity first arrived at or was initially present in a specified place or context.
-
C.
firstProductionYear
Indicates the year in which something (such as a product, work, or item) was first produced.
-
D.
firstModelIntroduced
Indicates that one entity is the earliest or original model introduced in relation to another entity or context.
-
E.
firstInstallmentYear
Indicates the year in which the first installment of a series of payments or releases occurs.
- 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_69f3493446148190819541f3ffe79975 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a0379f0cbe481909b4b8fc6cbe297f0 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:10 a.m.