Triple
T16287513
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Porter |
E395427
|
entity |
| Predicate | relatedToWord |
P10003
|
FINISHED |
| Object | port (gate, door) |
—
|
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: port (gate, door) | Statement: [Porter, relatedToWord, port (gate, door)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedToWord Context triple: [Porter, relatedToWord, port (gate, door)]
-
A.
relatedToTerm
Indicates a general, non-specific relationship or association between one term and another.
-
B.
linguisticallyRelatedTo
chosen
Indicates that two entities are connected through a linguistic relationship, such as sharing a common language, origin, structure, or other language-based association.
-
C.
relatedTo
Indicates a general, non-specific relationship or association exists between two entities.
-
D.
moreCloselyRelatedTo
Indicates that one entity has a stronger or closer relationship, connection, or similarity to a second entity than to some other reference entity.
-
E.
relatedMatchType
Indicates that two entities are connected through a specified type or category of relationship that defines how they are considered related or matched.
- 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_69d87f22c7248190a54c949738441e2e |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e24915a5948190a11b8e83b7974dda |
completed | April 17, 2026, 2:52 p.m. |
| PD | Predicate disambiguation | batch_69e219f68d308190b71c1601303f0628 |
completed | April 17, 2026, 11:31 a.m. |
Created at: April 10, 2026, 5:05 a.m.