Triple
T951520
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Princess Eléonore of Belgium |
E20532
|
entity |
| Predicate | alsoSpeaks |
P13756
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Princess Eléonore of Belgium, alsoSpeaks, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alsoSpeaks Context triple: [Princess Eléonore of Belgium, alsoSpeaks, English]
-
A.
alsoSpeak
chosen
Indicates that an entity, in addition to another language or mode of communication already mentioned, speaks this additional language or communicates in this additional way.
-
B.
languagesSpoken
Indicates that an entity is able to communicate using one or more specified languages.
-
C.
isSpokenAs
Indicates that one entity is used as the spoken or verbal form of another entity (e.g., a word, name, or phrase).
-
D.
commonsSpeaker
Indicates that a person serves as the Speaker (presiding officer) of the House of Commons.
-
E.
spokeAt
Indicates that a person delivered a talk, speech, or presentation at a particular event or location.
- 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_69a493b0f2fc81908cd227480a5356a1 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3d757d08190a475cf47febd05ae |
completed | March 1, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a045308190ab94f3adab40db8d |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.