Triple
T11939608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rafah–El Kantara line |
E284139
|
entity |
| Predicate | terminus |
P388
|
FINISHED |
| Object | El Kantara |
E811812
|
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: El Kantara | Statement: [Rafah–El Kantara line, terminus, El Kantara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: El Kantara Context triple: [Rafah–El Kantara line, terminus, El Kantara]
-
A.
El Kantara
chosen
El Kantara is a historic Algerian town famed for its dramatic gorge and strategic location linking the Sahara Desert to northern Algeria.
-
B.
Las Caletas
Las Caletas is a small coastal settlement on the southern part of La Palma in Spain’s Canary Islands, known for its volcanic landscapes and Atlantic shoreline.
-
C.
Karavola
Karavola is the summit that forms the highest peak of Mount Parnitha in Greece.
-
D.
Ontinyent
Ontinyent is a historic town in eastern Spain known for its textile industry, traditional festivals, and scenic setting along the Clariano River.
-
E.
La Mar
La Mar is an archaeological site in the western Maya lowlands known for its Classic-period Maya ruins and inscriptions.
- 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_69d6ab2ce9c48190b5d39511b524f666 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903415d2481909d84e6727454b9fe |
completed | April 10, 2026, 2:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f4409a40dc81909d87c50601b98b78 |
completed | May 1, 2026, 5:56 a.m. |
Created at: April 8, 2026, 9:45 p.m.