Triple
T236132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | His Majesty |
E4827
|
entity |
| Predicate | precedesName |
P5575
|
FINISHED |
| Object | the name of the reigning king |
—
|
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: the name of the reigning king | Statement: [His Majesty, precedesName, the name of the reigning king]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: precedesName Context triple: [His Majesty, precedesName, the name of the reigning king]
-
A.
predecessor
Indicates that one entity comes before another in an ordered sequence or succession.
-
B.
previousHonorificPrefix
chosen
Indicates that one entity was formerly used as an honorific prefix or title for another entity before being changed or replaced.
-
C.
predecessorTitleHolder
Indicates that one entity previously held a particular title or position before another entity.
-
D.
precedentFor
Indicates that one situation, decision, or case serves as an authoritative example or basis for deciding or interpreting another.
-
E.
namedAfter
Indicates that one entity has been given its name in honor of, or derived from, another entity.
- 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_69a257c3d0708190b0871c4269d273e6 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25ccab7648190be6e4f5febc1e313 |
completed | Feb. 28, 2026, 3:11 a.m. |
| PD | Predicate disambiguation | batch_69a25b5dc640819092669575731c393f |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.