Triple
T189474
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | deuteron |
E3686
|
entity |
| Predicate | hasMassNumber |
P5748
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [deuteron, hasMassNumber, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMassNumber Context triple: [deuteron, hasMassNumber, 2]
-
A.
isMassive
Indicates that one entity has an extremely large size, scale, or extent relative to typical or comparable entities.
-
B.
hasIsospin
Indicates that one particle possesses a specific isospin value or quantum number in relation to another reference or classification framework.
-
C.
hasMeanDensity
Indicates that one entity possesses a specified average mass per unit volume (mean density).
-
D.
hasWeakIsospin
Indicates that an entity possesses a specified value of weak isospin, representing its charge under the weak nuclear interaction.
-
E.
hasMeanRadius
Indicates that an entity possesses a specified average radius measurement, typically representing the mean distance from its center to its surface.
- 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_69a2548debd48190ae3a06d6e65b53c6 |
completed | Feb. 28, 2026, 2:35 a.m. |
| NER | Named-entity recognition | batch_69a2594c385481909e1e088e45c460a4 |
completed | Feb. 28, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69a25672332081909386f35f3ca15dd2 |
completed | Feb. 28, 2026, 2:44 a.m. |
| PDg | Predicate description generation | batch_69a25738b5108190866fd704fceee18a |
completed | Feb. 28, 2026, 2:47 a.m. |
Created at: Feb. 28, 2026, 2:41 a.m.