Triple
T36760959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stiffbeards |
E908198
|
entity |
| Predicate | hasKnownDetails |
P186270
|
FINISHED |
| Object | very limited |
—
|
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: very limited | Statement: [Stiffbeards, hasKnownDetails, very limited]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasKnownDetails Context triple: [Stiffbeards, hasKnownDetails, very limited]
-
A.
hasReferentKnownFor
Indicates that the referent (the thing being referred to) is known or notable for a particular characteristic, role, or achievement.
-
B.
hasUnknown
Indicates that an entity possesses or is associated with information, attributes, or values that are not known or not specified.
-
C.
knownToBe
Indicates that one entity is recognized or acknowledged as being a certain way, having a certain property, or fitting a particular description by others.
-
D.
hasKeyInformation
Indicates that an entity possesses or contains essential or critical information relevant to another entity, context, or task.
-
E.
hasHistoricalDetail
Indicates that something includes or is associated with specific information about past events, contexts, or developments.
- 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_69f76e779bec8190be0e1f87a131e0f4 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7cabacc1481909e839454ce1057f7 |
completed | May 3, 2026, 10:22 p.m. |
| PD | Predicate disambiguation | batch_69f7c8999a348190abc1895eaa6e036d |
completed | May 3, 2026, 10:13 p.m. |
| PDg | Predicate description generation | batch_69f7c9f4c7c48190ba918d8d5dc8dfd9 |
completed | May 3, 2026, 10:19 p.m. |
Created at: May 3, 2026, 4:12 p.m.