Triple
T7174475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AMD Sempron |
E167284
|
entity |
| Predicate | coreName |
P59725
|
FINISHED |
| Object | Sargas |
E472723
|
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: Sargas | Statement: [AMD Sempron, coreName, Sargas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sargas Context triple: [AMD Sempron, coreName, Sargas]
-
A.
Sargas
chosen
Sargas is a bright giant star in the constellation Scorpius, notable for its luminosity and relatively close distance to Earth.
-
B.
Mandraki
Mandraki is the main port town and one of the primary settlements on the Greek island of Hydra, known for its traditional architecture and seaside setting.
-
C.
Mandraki
Mandraki is the main town and administrative center of the Greek island of Nisyros, known for its traditional architecture and seaside setting.
-
D.
Wasquehal
Wasquehal is a suburban commune in northern France that forms part of the Lille metropolitan area.
-
E.
Thalassius
Thalassius is a figure or persona known primarily as the addressee of the ancient text "Questions to Thalassius," in which theological or philosophical questions are posed to him.
- 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_69c68889a2748190a316c5e65360361a |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e88d770c8190b8d06dcd08447c08 |
completed | March 27, 2026, 8:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7b921b1e48190b25c1337f6187174 |
completed | March 28, 2026, 11:18 a.m. |
Created at: March 27, 2026, 2:48 p.m.