Triple
T16871989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Main Street (Glen Ellyn, Illinois) |
E421190
|
entity |
| Predicate | isCommonNameOf |
P1354
|
FINISHED |
| Object | central commercial street in many U.S. towns |
—
|
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: central commercial street in many U.S. towns | Statement: [Main Street (Glen Ellyn, Illinois), isCommonNameOf, central commercial street in many U.S. towns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isCommonNameOf Context triple: [Main Street (Glen Ellyn, Illinois), isCommonNameOf, central commercial street in many U.S. towns]
-
A.
includesCommonName
Indicates that one entity contains or specifies a commonly used (non-scientific) name for another entity.
-
B.
commonNameOf
chosen
Indicates that one entity is the commonly used or popular name by which the other entity is known.
-
C.
commonName
Indicates that one entity is the commonly used or vernacular name by which the other entity is known.
-
D.
isCommonAsFirstName
Indicates that the referenced name is frequently used as a first (given) name within a specified population or context.
-
E.
otherCommonName
Indicates that an entity is known by an additional, alternative common name besides its primary one.
- 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_69d889d470fc8190b4aec199636c0c56 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3b7f31b448190a21e3e4d1a0d2f73 |
completed | April 18, 2026, 4:57 p.m. |
| PD | Predicate disambiguation | batch_69e32b90ec3c819099c51bb7baf2984c |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:29 a.m.