Triple
T35074257
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Argo Navis |
E1011966
|
entity |
| Predicate | wasLaterDividedBy |
P181952
|
FINISHED |
| Object | Nicolas-Louis de Lacaille |
—
|
NE NERFINISHED |
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: Nicolas-Louis de Lacaille | Statement: [Argo Navis, wasLaterDividedBy, Nicolas-Louis de Lacaille]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasLaterDividedBy Context triple: [Argo Navis, wasLaterDividedBy, Nicolas-Louis de Lacaille]
-
A.
wasDividedAfter
chosen
Indicates that one entity was split into parts or separate entities following a specified event or point in time.
-
B.
wasDividedBetween
Indicates that something was partitioned into portions that were allocated to two or more distinct recipients or groups.
-
C.
dividedBy
Indicates that one quantity is separated into a specified number of equal parts or groups by another quantity, representing a division relationship between them.
-
D.
wasDividedFrom
Indicates that one entity was separated or split off from another entity, resulting in two distinct parts or groups.
-
E.
dividedIn
Indicates that one entity is partitioned or separated into multiple distinct parts, sections, or groups represented by 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_69f76dd193108190af2528186f25b72a |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78658f6fc8190ba08ce880a6568e5 |
completed | May 3, 2026, 5:31 p.m. |
| PD | Predicate disambiguation | batch_69f7841812f081909d878955d114088e |
completed | May 3, 2026, 5:21 p.m. |
Created at: May 3, 2026, 4:01 p.m.