Triple
T15906402
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al-Khazneh |
E385731
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Petra |
E83222
|
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: Petra | Statement: [Al-Khazneh, locatedIn, Petra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Petra Context triple: [Al-Khazneh, locatedIn, Petra]
-
A.
Petra
chosen
Petra is an ancient rock-cut city in southern Jordan renowned for its monumental sandstone architecture and role as the former capital of the Nabataean Kingdom.
-
B.
Petra
Petra is a brave and skilled warrior character from the episodic adventure game Minecraft: Story Mode, known for her combat prowess and loyalty to her friends.
-
C.
Petra
Petra is a character in the romantic comedy film "Last Christmas," which is inspired by the music of George Michael and Wham!.
-
D.
Ko Petra
Ko Petra is a small, scenic island in Thailand’s Trang Province, known for its limestone cliffs, clear waters, and tranquil, less-developed beaches.
-
E.
Saqqez
Saqqez is a historically significant Kurdish city in western Iran known as one of the main urban centers of Kurdistan Province.
- 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_69d86da686e4819097cbf3b1fc2d881d |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1565b0d688190acc181c777387c65 |
completed | April 16, 2026, 9:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb0535a808190983b4ff028826cbf |
completed | May 9, 2026, 10:08 p.m. |
Created at: April 10, 2026, 4:52 a.m.