Triple
T35478067
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Inheritance Part 2 |
E1025389
|
entity |
| Predicate | firstMajorProductionCity |
P47743
|
FINISHED |
| Object | London |
E1817
|
NE 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 | Statement: [The Inheritance Part 2, firstMajorProductionCity, London]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstMajorProductionCity Context triple: [The Inheritance Part 2, firstMajorProductionCity, London]
-
A.
firstMajorRunCity
Indicates the city where an entity’s first major run, performance, or large-scale event initially took place.
-
B.
otherMajorCity
Indicates that one city is another major city associated with or comparable in importance or status to the first city.
-
C.
primaryCity
Indicates that one city serves as the main or most important city associated with a given region, entity, or context.
-
D.
principalCityOf
Indicates that a city serves as the main or most important city (often administrative, economic, or cultural center) of a specified region or area.
-
E.
firstMajorProductionLocation
chosen
Indicates the location where an entity’s first major production or large-scale manufacturing activity took place.
- F. None of above.
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_69f76dfadba0819083456aadcd6864ea |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037c8d06cc8190ab6a5e18d9d2571e |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a384a23d9c881908280b3e002ad881b |
completed | June 21, 2026, 8:31 p.m. |
| PD | Predicate disambiguation | batch_6a037a0324d08190ac5b610cc0f6a38c |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:04 p.m.