Triple
T19338292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Delbert |
E483679
|
entity |
| Predicate | possibleElement |
P135473
|
FINISHED |
| Object | Del- |
—
|
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: Del- | Statement: [Delbert, possibleElement, Del-]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: possibleElement Context triple: [Delbert, possibleElement, Del-]
-
A.
usesElement
Indicates that one entity makes use of, incorporates, or depends on a specified element in its structure, function, or behavior.
-
B.
chanceElement
Indicates that the relationship or outcome involves randomness or probabilistic chance rather than being deterministic.
-
C.
possibleValue
Indicates that a given value is one of the allowed or valid options for a particular attribute, parameter, or variable.
-
D.
possibleFunction
Indicates that an entity may serve, or is capable of serving, a particular function or role, without asserting that it actually does so.
-
E.
possibleModel
Indicates that one entity can serve as a potential or candidate model or template for another entity.
- 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_69d8e8d244f8819080eb1f3491300db2 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e6185538d48190ae4fa3ac0b0ca182 |
completed | April 20, 2026, 12:13 p.m. |
| PD | Predicate disambiguation | batch_69e4dd12303c8190a2027c062b2dff40 |
completed | April 19, 2026, 1:48 p.m. |
| PDg | Predicate description generation | batch_69e4df51ac6c819091ce72b07790ffa6 |
completed | April 19, 2026, 1:57 p.m. |
Created at: April 10, 2026, 1:33 p.m.