Triple
T22999228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lesser Dog |
E572588
|
entity |
| Predicate | hasRankByArea |
P150581
|
FINISHED |
| Object | 71st of the 88 constellations |
—
|
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: 71st of the 88 constellations | Statement: [Lesser Dog, hasRankByArea, 71st of the 88 constellations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRankByArea Context triple: [Lesser Dog, hasRankByArea, 71st of the 88 constellations]
-
A.
hasHighestAreas
Indicates that the subject possesses the largest or most extensive areas compared to other relevant entities or regions.
-
B.
floorAreaRank
Indicates the relative ordering of entities based on the size of their floor area, with lower ranks representing larger floor areas.
-
C.
hasAreaRankInTaiwan
Indicates the relative ranking of an entity by its area size compared to other entities within Taiwan.
-
D.
hasLandmarkArea
Indicates that a specified area is designated as the landmark area associated with a particular entity or location.
-
E.
hasAreaRange
Indicates that something’s area falls within a specified minimum-to-maximum range.
- 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_69e245b6a3ac81908087599eefe3e365 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f182f6484c8190bfe3f7ea894c43d8 |
completed | April 29, 2026, 4:03 a.m. |
| PD | Predicate disambiguation | batch_69ef3b974e7c8190b8be11dbb4518693 |
completed | April 27, 2026, 10:33 a.m. |
| PDg | Predicate description generation | batch_69ef538b29c081908fa56ee35a1dcee7 |
completed | April 27, 2026, 12:16 p.m. |
Created at: April 17, 2026, 3:50 p.m.