Triple
T2336656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mike and Nan sectors |
E44325
|
entity |
| Predicate | hasCodeNameRole |
P6015
|
FINISHED |
| Object | landing areas |
—
|
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: landing areas | Statement: [Mike and Nan sectors, hasCodeNameRole, landing areas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCodeNameRole Context triple: [Mike and Nan sectors, hasCodeNameRole, landing areas]
-
A.
hasCodeName
chosen
Indicates that an entity is known or referred to by a particular alternative name or alias, often used for secrecy or distinction.
-
B.
hasCodenameLanguage
Indicates that a codename is expressed or defined in a particular language.
-
C.
hasEquivalentRole
Indicates that two entities hold roles that are functionally the same or interchangeable in a given context.
-
D.
hasCodeScheme
Indicates that something is associated with or organized according to a particular coding or classification scheme.
-
E.
hasComponentName
Indicates that an entity includes or is associated with a component identified by a specific name.
- 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_69a889132b488190bbb43ad4780ddd92 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abc6f75d888190a2e41edaa532e83f |
completed | March 7, 2026, 6:34 a.m. |
| PD | Predicate disambiguation | batch_69abc594087c819098100a10c5478a4b |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:51 p.m.