Triple
T475271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Neeleman |
E9046
|
entity |
| Predicate | hasDualCitizenship |
P13473
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [David Neeleman, hasDualCitizenship, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDualCitizenship Context triple: [David Neeleman, hasDualCitizenship, true]
-
A.
countryOfCitizenship
Indicates the country in which a person or entity holds legal citizenship.
-
B.
laterCitizenship
Indicates that an entity acquired citizenship in a country or polity at a later point in time, after some earlier status or affiliation.
-
C.
namedAfterCountryOfCitizenship
Indicates that something is named after the country where a person holds citizenship.
-
D.
hasSovereignState
Indicates that one entity is the sovereign state that has ultimate authority or jurisdiction over another entity.
-
E.
acquireCitizenshipBy
Indicates the process or means by which an entity obtains or is granted citizenship through a specific method, action, or legal basis.
- 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_69a2e7ff81708190b0507a24a997232c |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2f03b5e5081908ee3dba9d19a6871 |
completed | Feb. 28, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_69a2edeed31881908cf43beed410572d |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2eeba8a488190986cc7381332f783 |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.