Triple
T36378193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Countess of Dalhousie |
E895966
|
entity |
| Predicate | usedAsSpousalTitle |
P77742
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Countess of Dalhousie, usedAsSpousalTitle, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedAsSpousalTitle Context triple: [Countess of Dalhousie, usedAsSpousalTitle, yes]
-
A.
isSpouseOfTitle
Indicates that one entity holds a spousal relationship specifically associated with a titled or honorific status of another entity.
-
B.
titleFromSpouse
chosen
Indicates that an entity holds a title or honorific that is derived from or acquired through their spouse.
-
C.
hasSpouseTitle
Indicates that a person’s spouse holds a particular title or honorific designation.
-
D.
spouseNameWithTitle
Indicates that a person’s spouse is identified by name together with an associated honorific or title.
-
E.
titleHolderSpouseHouse
Indicates that the spouse of the current title holder is associated with or belongs to a particular house or family line.
- 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_69f76e51d358819092bbc5f119f49476 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fed357b2b4819084c709056a54461f |
completed | May 9, 2026, 6:25 a.m. |
| PD | Predicate disambiguation | batch_69fed103d9cc81909b11619745110c61 |
completed | May 9, 2026, 6:15 a.m. |
Created at: May 3, 2026, 4:10 p.m.