Triple
T37797507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unnamed daughter of Philip of Swabia and Irene Angelina |
E942258
|
entity |
| Predicate | hasNoSurvivingNameRecord |
P204182
|
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: [Unnamed daughter of Philip of Swabia and Irene Angelina, hasNoSurvivingNameRecord, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNoSurvivingNameRecord Context triple: [Unnamed daughter of Philip of Swabia and Irene Angelina, hasNoSurvivingNameRecord, true]
-
A.
hasNoSurvivingRecordings
Indicates that there are no existing audio or video recordings known to have survived for the referenced subject or event.
-
B.
hasNoLongerExistsAs
Indicates that an entity previously existed in a certain form, state, or identity but no longer exists in that form.
-
C.
hasNoPersonalNameIn
Indicates that an entity lacks a specific personal name within a given context, language, or naming system.
-
D.
hasNoCharactersWithNames
Indicates that the subject entity does not contain any characters for whom explicit names are specified.
-
E.
hasNoGivenName
chosen
Indicates that an entity lacks a specified or recorded given (first) name in the described context.
- 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_69f76ee6f1f4819091e2cf9c9e6aee19 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a1772e48190ba738c6d11b321e2 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:19 p.m.