Triple
T34775934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McMinnville UFO photographs |
E1002505
|
entity |
| Predicate | languageOfEarlyCoverage |
P38135
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [McMinnville UFO photographs, languageOfEarlyCoverage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfEarlyCoverage Context triple: [McMinnville UFO photographs, languageOfEarlyCoverage, English]
-
A.
languageOfCoverage
chosen
Indicates the language in which the coverage, such as reporting or documentation about something, is expressed.
-
B.
languageOfEarlyServices
Indicates the language in which early services (such as initial or preliminary sessions, programs, or interventions) are conducted.
-
C.
languageFamilyCoverage
Indicates the extent to which a given entity (such as a resource, model, or system) supports or covers the languages within a specified language family.
-
D.
languageOfProvision
Indicates the language in which a provision, such as a legal or contractual clause, is written or officially expressed.
-
E.
languageOfEarlyDevelopment
Indicates that a specified language is used during the initial or formative stages of an entity’s development.
- 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_69f76db30a108190bb57ca95b873e5bb |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_6a0087de41c48190b2743a26b6d65409 |
completed | May 10, 2026, 1:27 p.m. |
| PD | Predicate disambiguation | batch_6a00870a8bc48190be1385579b8cc1dd |
completed | May 10, 2026, 1:24 p.m. |
Created at: May 3, 2026, 3:59 p.m.