Triple
T29323653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L’Incorruptible |
E743580
|
entity |
| Predicate | hasAmbiguousReception |
P166841
|
FINISHED |
| Object | admired by some historians |
—
|
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: admired by some historians | Statement: [L’Incorruptible, hasAmbiguousReception, admired by some historians]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAmbiguousReception Context triple: [L’Incorruptible, hasAmbiguousReception, admired by some historians]
-
A.
hasAmbiguous
Indicates that the relationship or state is unclear, uncertain, or open to multiple interpretations.
-
B.
hasReception
Indicates that an entity hosts, includes, or is associated with a reception event (such as a formal gathering or welcoming function).
-
C.
hasReceiver
Indicates that an entity serves as the recipient or target of something provided, sent, or directed by another entity.
-
D.
hasAmbiguousEnding
Indicates that the event, story, or situation concludes in a way that is open to multiple interpretations or lacks a clear, definitive resolution.
-
E.
hasAmbiguousIdentity
Indicates that an entity’s identity is unclear, uncertain, or can be interpreted in multiple distinct ways.
- 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_69f09125f784819080f4e9fce9fe624f |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69f6689407bc8190b801c02fcb6e0e9a |
completed | May 2, 2026, 9:11 p.m. |
| PD | Predicate disambiguation | batch_69f660f2e3708190ab658652bcfc04d0 |
completed | May 2, 2026, 8:39 p.m. |
| PDg | Predicate description generation | batch_69f661e9cb308190a56e25dc17df248e |
completed | May 2, 2026, 8:43 p.m. |
Created at: April 28, 2026, 1:25 p.m.