Triple
T26223102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pedro da Covilhã |
E655814
|
entity |
| Predicate | statusInEthiopia |
P178759
|
FINISHED |
| Object | royal advisor |
—
|
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: royal advisor | Statement: [Pedro da Covilhã, statusInEthiopia, royal advisor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: statusInEthiopia Context triple: [Pedro da Covilhã, statusInEthiopia, royal advisor]
-
A.
populationRankInEthiopia
Indicates the relative position of an entity in terms of population size compared to other entities within Ethiopia.
-
B.
statusInGhana
Indicates the legal, social, or official standing or condition an entity holds within the context of Ghana.
-
C.
statusInEgypt
Indicates the legal, social, or official condition or standing that an entity holds specifically within the context of Egypt.
-
D.
distanceFromAddisAbaba
Indicates the physical distance between a given location and Addis Ababa.
-
E.
statusInBurkinaFaso
Indicates the legal, social, or official condition or standing that an entity has within the context of Burkina Faso.
- 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_69ee5b4a77e08190bfcb5f8ecdc55abd |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f71422adac8190a5ceb32dcf820833 |
completed | May 3, 2026, 9:23 a.m. |
| PD | Predicate disambiguation | batch_69f712764d2c819081b64b27e5de4a13 |
completed | May 3, 2026, 9:16 a.m. |
| PDg | Predicate description generation | batch_69f71421e8d08190807ccfb15d0f0ddb |
completed | May 3, 2026, 9:23 a.m. |
Created at: April 26, 2026, 8:57 p.m.