Triple
T504728
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Boar’s Head Tavern, Eastcheap |
E10478
|
entity |
| Predicate | partOfFictionalCity |
P14483
|
FINISHED |
| Object | London in Shakespeare’s histories |
—
|
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: London in Shakespeare’s histories | Statement: [The Boar’s Head Tavern, Eastcheap, partOfFictionalCity, London in Shakespeare’s histories]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfFictionalCity Context triple: [The Boar’s Head Tavern, Eastcheap, partOfFictionalCity, London in Shakespeare’s histories]
-
A.
basedInCity
Indicates that an entity has its primary location, headquarters, or main operations situated in a specified city.
-
B.
partOfMetropolitanArea
Indicates that one place is included within and belongs to the larger metropolitan area of another place.
-
C.
city1
Indicates that the subject is classified as a city.
-
D.
city2
Indicates a relationship where one entity is identified as a city associated with, located in, or otherwise linked to another entity.
-
E.
isMajorCityIn
Indicates that a city is a primary or significant urban center located within a specified larger region or country.
- 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_69a2e848adf881908e5e04f7af030093 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f149bd1c81908ff58ac504ace2bf |
completed | Feb. 28, 2026, 1:44 p.m. |
| PD | Predicate disambiguation | batch_69a2edfce7a08190a408bc019de60d5d |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2eebbd70481908b462296671de67b |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.