Triple
T396593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Seal of the United States |
E8995
|
entity |
| Predicate | numberOfStarsInConstellation |
P10942
|
FINISHED |
| Object | 13 |
—
|
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: 13 | Statement: [Great Seal of the United States, numberOfStarsInConstellation, 13]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfStarsInConstellation Context triple: [Great Seal of the United States, numberOfStarsInConstellation, 13]
-
A.
approximateStellarCount
Indicates an estimated or rough number of stars associated with a given astronomical object or region.
-
B.
numberOfBrightNakedEyeStars
Indicates the count of stars that are bright enough to be seen with the naked eye.
-
C.
starCount
Indicates the number of stars associated with an entity, typically representing a rating, quality level, or count of starred items.
-
D.
relatedConstellation
Indicates a relationship where one entity is associated with, connected to, or corresponds to a particular constellation.
-
E.
brightestStar
Indicates that one entity is the most luminous star within a specified group, region, or context relative to the others.
- 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_69a2e7f55c60819097aff65ea2ca2832 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec8a941081909a152fda0ce24a98 |
completed | Feb. 28, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69a2e96d17d08190878d3a68b17d51ca |
completed | Feb. 28, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69a2ea4545608190898436c72e10f39d |
completed | Feb. 28, 2026, 1:14 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.