Triple
T25070226
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Langholm, North Carolina |
E627887
|
entity |
| Predicate | hasSymbolicConnectionTo |
P43975
|
FINISHED |
| Object | Neil Armstrong |
—
|
NE NERFINISHED |
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: Neil Armstrong | Statement: [Langholm, North Carolina, hasSymbolicConnectionTo, Neil Armstrong]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSymbolicConnectionTo Context triple: [Langholm, North Carolina, hasSymbolicConnectionTo, Neil Armstrong]
-
A.
hasSymbolicRelationshipType
Indicates that there exists a symbolic (non-literal) relationship of a specified type between two entities.
-
B.
hasNotableConnectionTo
chosen
Indicates a significant or noteworthy relationship, association, or link exists between two entities.
-
C.
containsSymbolicAct
Indicates that one entity includes or incorporates a symbolic action or gesture associated with another entity.
-
D.
connectsTo
Indicates a relationship where one entity is linked or joined to another, allowing interaction, communication, or transfer between them.
-
E.
hasRelationSymbol
Indicates that there exists a specific relational operator or symbol used to denote the relationship between entities.
- 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_69e2ff2d71dc8190b4758e57d643cbe4 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f45d13c684819085690724d772616e |
completed | May 1, 2026, 7:58 a.m. |
| PD | Predicate disambiguation | batch_69f442c861188190967655c6d8012380 |
completed | May 1, 2026, 6:06 a.m. |
Created at: April 18, 2026, 6:10 a.m.