Triple
T13763290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jacques, Hereditary Prince of Monaco |
E330668
|
entity |
| Predicate | twinOrder |
P110861
|
FINISHED |
| Object | born after his twin sister |
—
|
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: born after his twin sister | Statement: [Jacques, Hereditary Prince of Monaco, twinOrder, born after his twin sister]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: twinOrder Context triple: [Jacques, Hereditary Prince of Monaco, twinOrder, born after his twin sister]
-
A.
twinType
Indicates that one entity is classified as a specific type or category of twin in relation to another entity.
-
B.
twinning
Indicates that two entities are paired or linked as twins, typically sharing a formally recognized, parallel, or closely matched relationship.
-
C.
isTwinWith
Indicates that two entities are twins, sharing the same birth parents and being born at (or very near) the same time.
-
D.
joinedOrderOf
Indicates that an entity became a member of, or formally joined, a particular order or organization.
-
E.
hasTwin
Indicates that one entity is a twin of another, sharing the same birth event or time with a sibling.
- 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_69d81c583b0081909e408a17db517a21 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de022690ac8190bd5410ecc659a2a7 |
completed | April 14, 2026, 9 a.m. |
| PD | Predicate disambiguation | batch_69dbbe97846c819093b00ea117b64e0d |
completed | April 12, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69dbc59db0148190bcaf9646403ca64f |
completed | April 12, 2026, 4:17 p.m. |
Created at: April 9, 2026, 10:10 p.m.