Triple
T21050697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Panagia tou Harou church |
E518571
|
entity |
| Predicate | pilgrimsComeFrom |
P57386
|
FINISHED |
| Object | Lipsi |
—
|
NE NERFINISHED |
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: Lipsi | Statement: [Panagia tou Harou church, pilgrimsComeFrom, Lipsi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lipsi Context triple: [Panagia tou Harou church, pilgrimsComeFrom, Lipsi]
-
A.
Lipsi
chosen
Lipsi is a small Greek island in the southeastern Aegean Sea, known for its tranquil atmosphere, traditional villages, and unspoiled beaches.
-
B.
Lapincs
Lapincs is a river in Central Europe that serves as a tributary of the Rába River.
-
C.
Pulastya
Pulastya is one of the seven great sages (Saptarishi) in Hindu tradition, revered as a mind-born son of Brahma and an important progenitor in various mythological lineages.
-
D.
Lipski
Lipski is a Polish surname borne by various notable figures in politics, arts, and academia.
-
E.
Luntai
Luntai is a small oasis town and county in China’s Xinjiang region, situated along the northern edge of the Taklamakan Desert on the historic Silk Road.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b5053ac48190921529544959e906 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fd7a5cf48190939aefaa44db1ddb |
completed | April 21, 2026, 4:30 a.m. |
Created at: April 16, 2026, 2:35 p.m.