Triple
T36611769
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King’s Men of Númenor |
E903482
|
entity |
| Predicate | rejectedLanguage |
P186069
|
FINISHED |
| Object | Quenya |
—
|
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: Quenya | Statement: [King’s Men of Númenor, rejectedLanguage, Quenya]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rejectedLanguage Context triple: [King’s Men of Númenor, rejectedLanguage, Quenya]
-
A.
rejectedBy
Indicates that one entity has been refused, dismissed, or not accepted by another entity.
-
B.
rejectedIn
Indicates that an entity or proposal was not accepted or was turned down within a specific context, process, or location.
-
C.
rejectedBecause
Indicates that one entity refused, dismissed, or did not accept another entity specifically due to a stated reason or cause.
-
D.
rejectedAt
Indicates the time or date at which something (such as a request, application, or proposal) was formally rejected.
-
E.
rejectLabel
Indicates that one entity refuses to accept, approve, or assign a particular label or classification to another entity.
- F. None of above. chosen
Provenance (4 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_69f76e6960e4819092047756ceb9a17e |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c83f5960819089610ed39c839678 |
completed | May 3, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69f7c477a4d481908f52e55b6688f60c |
completed | May 3, 2026, 9:56 p.m. |
| PDg | Predicate description generation | batch_69f7c776b4088190bef550c869da530d |
completed | May 3, 2026, 10:08 p.m. |
Created at: May 3, 2026, 4:11 p.m.