Triple
T605507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charles Stark Draper Prize for Engineering |
E11584
|
entity |
| Predicate | namedForField |
P17009
|
FINISHED |
| Object | guidance and control engineering |
—
|
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: guidance and control engineering | Statement: [Charles Stark Draper Prize for Engineering, namedForField, guidance and control engineering]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: namedForField Context triple: [Charles Stark Draper Prize for Engineering, namedForField, guidance and control engineering]
-
A.
namedAfterField
Indicates that one entity has been given a name derived from or in honor of another entity, typically a person, place, or thing.
-
B.
fieldName
Indicates the specific name or label assigned to a field within a data structure, form, or record.
-
C.
namedAfter
Indicates that one entity has been given its name in honor of, or derived from, another entity.
-
D.
givenNameFor
Indicates that one entity is the personal first name assigned to or used for another entity.
-
E.
coNamedWith
Indicates that two or more entities share the same name or are designated by an identical label.
- 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_69a4932779b881908688590d59c71900 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49df34abc8190a578c8c2ab3d28e4 |
completed | March 1, 2026, 8:13 p.m. |
| PD | Predicate disambiguation | batch_69a49cf8fc1c81908a9c7df552aa1a59 |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49def31ec81909dc53e70f4a36eda |
completed | March 1, 2026, 8:13 p.m. |
Created at: March 1, 2026, 7:35 p.m.