Triple
T23492637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hauran plateau |
E571617
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Lajat |
—
|
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: Lajat | Statement: [Hauran plateau, hasPart, Lajat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lajat Context triple: [Hauran plateau, hasPart, Lajat]
-
A.
Lajat
chosen
Lajat is a volcanic plateau in southern Syria known for its rugged basalt landscape and ancient archaeological sites.
-
B.
Lajen
Lajen is a small municipality in South Tyrol in northern Italy, known for its alpine scenery and blend of German and Italian cultural influences.
-
C.
Lasat
Lasat are a powerful, agile, and spiritually inclined sentient species from the Star Wars universe, known for their warrior traditions and distinctive, tall, fur-covered appearance.
-
D.
Laukaa
Laukaa is a municipality in Central Finland known for its lakes, rural landscapes, and proximity to the city of Jyväskylä.
-
E.
Laja
Laja is a small Chilean city in the Biobío Region, known for its riverside setting and proximity to the Biobío River.
- 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_69e245b4829881909b77a70e942bbd54 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a7dd56408190b459077e433ed1c3 |
completed | April 29, 2026, 6:40 a.m. |
Created at: April 17, 2026, 6:05 p.m.