Triple
T23087858
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lowndes Square |
E575660
|
entity |
| Predicate | hasNotableTypeOfResident |
P5947
|
FINISHED |
| Object | diplomats |
—
|
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: diplomats | Statement: [Lowndes Square, hasNotableTypeOfResident, diplomats]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableTypeOfResident Context triple: [Lowndes Square, hasNotableTypeOfResident, diplomats]
-
A.
hasNotableResident
Indicates that an entity is or has been a well-known or distinguished resident of a particular place or location.
-
B.
hasNonHumanResident
Indicates that a place or location is inhabited or occupied by one or more non-human entities.
-
C.
hasResidentPopulation
Indicates that a place or administrative area has a population of people who live there permanently or for an extended period.
-
D.
hasNotablePopulation
Indicates that an entity is recognized for having a significant or noteworthy number of inhabitants or members.
-
E.
hasPopulationType
chosen
Indicates that an entity’s population is classified according to a specific type or category (e.g., demographic, biological, or statistical grouping).
- 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_69e245bf3e3c819086d3448720efc01b |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18da7c54c81908b62d04ab1811b06 |
completed | April 29, 2026, 4:48 a.m. |
| PD | Predicate disambiguation | batch_69ef89e5ce748190b2c3ac3843484127 |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 17, 2026, 3:57 p.m.