Triple
T37852400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sikorsky S-43 |
E944089
|
entity |
| Predicate | civilRegistrationExample |
P171666
|
FINISHED |
| Object | NC-16934 |
—
|
NE NERFINISHED |
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: NC-16934 | Statement: [Sikorsky S-43, civilRegistrationExample, NC-16934]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: civilRegistrationExample Context triple: [Sikorsky S-43, civilRegistrationExample, NC-16934]
-
A.
civilRegistration
Indicates the official recording of a person’s vital life event (such as birth, marriage, or death) by a civil authority.
-
B.
civilRegistrationCategory
Indicates the specific type or classification of a civil registration event or record associated with an entity.
-
C.
civilRegistrationCodeOf
chosen
Indicates that one entity is the civil registration code assigned to identify another entity in official civil records.
-
D.
civilRegistrationPrefixExample
Indicates that there is an example of a standard prefix used in civil registration identifiers or records.
-
E.
religiousRegister
Indicates that the relationship or action is expressed using language, style, or conventions specific to a religious context or practice.
- 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_69f76eed4d9c81908b1b71ba9e3b61fe |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbbae559a8819086ef839973f8d9b2 |
completed | May 6, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69fbb1440fa08190abf25ba684f75b6e |
completed | May 6, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:19 p.m.