Triple
T29524977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Order of the Queen of Sheba (Ethiopia) |
E749042
|
entity |
| Predicate | classOfRecipients |
P485
|
FINISHED |
| Object | high-ranking women |
—
|
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: high-ranking women | Statement: [Order of the Queen of Sheba (Ethiopia), classOfRecipients, high-ranking women]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: classOfRecipients Context triple: [Order of the Queen of Sheba (Ethiopia), classOfRecipients, high-ranking women]
-
A.
scopeOfRecipients
chosen
Indicates the range or group of recipients to whom something (such as information, communication, or benefits) is directed or applicable.
-
B.
locationOfRecipients
Indicates the place or geographic area where the intended recipients of something are situated.
-
C.
totalRecipients
Indicates the total number of distinct entities that receive something in the context of the described relationship or action.
-
D.
hasTypeOfRecipient
Indicates that an entity is associated with a specific category or kind of recipient it is intended for or directed to.
-
E.
addresseeType
Indicates the role or category of the entity that is the intended recipient or target of a communication or message.
- 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_69f0bd46d99c81908ba9d01cc1dbef7d |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69f67f7efc3c8190986d2d95b7a23729 |
completed | May 2, 2026, 10:49 p.m. |
| PD | Predicate disambiguation | batch_69f67e40af9881908de3a4aa15f70a83 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 28, 2026, 4:44 p.m.