Triple
T32838808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Algerian diaspora |
E839906
|
entity |
| Predicate | hasNotableConcentrationInCity |
P34971
|
FINISHED |
| Object | Paris |
E568
|
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: Paris | Statement: [Algerian diaspora, hasNotableConcentrationInCity, Paris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableConcentrationInCity Context triple: [Algerian diaspora, hasNotableConcentrationInCity, Paris]
-
A.
concentratedInCity
chosen
Indicates that a large proportion or primary presence of something is located within a particular city.
-
B.
hasPopulationConcentrationIn
Indicates that a population is densely or significantly clustered within a specified geographic area or region.
-
C.
notableDistrictConcentration
Indicates that a notable or significant concentration of something (such as people, activities, or features) is present within a particular district.
-
D.
notableStateConcentration
Indicates that a significant portion of the instances or activity of something is concentrated within a particular state or region.
-
E.
notableInCity
Indicates that an entity is particularly prominent, recognized, or significant within a specific city.
- 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_69f3493ff0888190b51e974eae2a7834 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a014f7602988190b8f86cb431a9cf12 |
completed | May 11, 2026, 3:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a34bceb22cc8190be7b2ef983864590 |
completed | June 19, 2026, 3:52 a.m. |
| PD | Predicate disambiguation | batch_6a014a70ea748190bd86fb9f218103ba |
completed | May 11, 2026, 3:18 a.m. |
Created at: May 1, 2026, 1:16 a.m.