Triple
T5551246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eris |
E145529
|
entity |
| Predicate | sibling |
P363
|
FINISHED |
| Object | Moros |
E249770
|
NE 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: Moros | Statement: [Eris, sibling, Moros]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Moros Context triple: [Eris, sibling, Moros]
-
A.
Moros
chosen
Moros is the personification of impending doom and fate in Greek mythology.
-
B.
Moro
Moro is a local government area in Kwara State, Nigeria, known for its predominantly rural communities and agricultural activities.
-
C.
Moro
The Moro are a collective term for several Muslim ethnolinguistic groups in the southern Philippines, particularly in Mindanao and the Sulu Archipelago, with a distinct history, culture, and struggle for self-determination.
-
D.
Matarranya
Matarranya is a rural comarca in the province of Teruel, Aragon, Spain, known for its scenic river valley landscapes, historic villages, and traditional agriculture.
-
E.
Mutasa
Mutasa is a town located in Zimbabwe’s eastern Manicaland Province, known for its rural communities and proximity to the Eastern Highlands.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c008fb879c81909f5bfa56fadc1d46 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01fe3e7788190aa5361b083197c17 |
completed | March 22, 2026, 4:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c028350bc08190a8b48893157b86a1 |
completed | March 22, 2026, 5:34 p.m. |
Created at: March 22, 2026, 3:35 p.m.