Triple
T35374759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shoemaker (namesake unknown) |
E1021874
|
entity |
| Predicate | hasNamesakeBuilding |
P49744
|
FINISHED |
| Object | Shoemaker Building |
—
|
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: Shoemaker Building | Statement: [Shoemaker (namesake unknown), hasNamesakeBuilding, Shoemaker Building]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNamesakeBuilding Context triple: [Shoemaker (namesake unknown), hasNamesakeBuilding, Shoemaker Building]
-
A.
hasBuildingNamedAfterHim
chosen
Indicates that a person has a building that is named in their honor.
-
B.
notableBuildingAssociated
Indicates a relationship where a notable or significant building is associated with, connected to, or relevant to a given entity.
-
C.
hasFamousStructure
Indicates that an entity possesses or is associated with a well-known or widely recognized structure.
-
D.
hasFamousNamesake
Indicates that an entity shares its name with another well-known or notable entity.
-
E.
eraOfManyBuildings
Indicates a time period during which many buildings were constructed or existed.
- 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_69f76df000488190ab7c97f565677055 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff41645c548190b7cb4e53079b93ef |
completed | May 9, 2026, 2:15 p.m. |
| PD | Predicate disambiguation | batch_69ff410aa33c8190869ba769ac2a93ce |
completed | May 9, 2026, 2:13 p.m. |
Created at: May 3, 2026, 4:03 p.m.