Triple
T21179827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baronet Montgomery |
E521916
|
entity |
| Predicate | rankComparedToKnighthood |
P80950
|
FINISHED |
| Object | above knight |
—
|
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: above knight | Statement: [Baronet Montgomery, rankComparedToKnighthood, above knight]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankComparedToKnighthood Context triple: [Baronet Montgomery, rankComparedToKnighthood, above knight]
-
A.
knighthoodStatus
Indicates whether an entity currently holds, has held, or has been granted a formal knighthood or equivalent honorific status.
-
B.
rankBeforeKingship
Indicates that one entity held a higher or earlier rank or status than another entity prior to that other entity attaining kingship.
-
C.
rankRelativeToPeerage
Indicates how an entity’s hierarchical rank compares to that of a specified peer or peer group within a defined ranking system.
-
D.
nobleRankInHierarchy
chosen
Indicates the relative position or level of a noble title within a structured hierarchy of ranks.
-
E.
rankComparedToLegionOfHonour
Indicates how the rank or level associated with something compares to the corresponding rank within the French Legion of Honour system.
- 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_69e0b50ef1d48190b063aa342667df22 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7301c842c8190b969a8b3f194003a |
completed | April 21, 2026, 8:06 a.m. |
| PD | Predicate disambiguation | batch_69e5f6027c248190a170a36612bd337e |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 3:01 p.m.