Triple
T189495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | deuteron |
E3686
|
entity |
| Predicate | hasAlternativeSymbol |
P129
|
FINISHED |
| Object | ^2H nucleus |
—
|
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: ^2H nucleus | Statement: [deuteron, hasAlternativeSymbol, ^2H nucleus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAlternativeSymbol Context triple: [deuteron, hasAlternativeSymbol, ^2H nucleus]
-
A.
hasOppositeNumberForm
Indicates that one entity is represented by a number form that is the opposite (e.g., additive vs. subtractive, positive vs. negative, or otherwise contrastive) of the number form used to represent the other entity.
-
B.
hasExonym
Indicates that one entity is known by an alternative name or designation in another language or cultural context.
-
C.
hasVariant
Indicates that one entity exists as an alternative form, version, or variation of another entity.
-
D.
hasVariantSpelling
Indicates that one term is an alternative spelling form of another term.
-
E.
symbolizes
chosen
Indicates that one entity stands for, represents, or is used as a sign for another entity, concept, or idea.
- 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_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_69a25673ce3c8190b1a3df5b814a0595 |
completed | Feb. 28, 2026, 2:44 a.m. |
Created at: Feb. 28, 2026, 2:41 a.m.