Triple
T4659835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deira |
E102501
|
entity |
| Predicate | knownFor |
P22
|
FINISHED |
| Object | gold souk |
E113405
|
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: gold souk | Statement: [Deira, knownFor, gold souk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: gold souk Context triple: [Deira, knownFor, gold souk]
-
A.
Gold Souq
Gold Souq is a traditional market area in Doha renowned for its numerous shops selling gold jewelry and other precious ornaments.
-
B.
Dubai Gold Souk
chosen
Dubai Gold Souk is a famous traditional market in Dubai renowned for its dense concentration of shops selling gold, jewelry, and precious stones.
-
C.
GOLD
GOLD is the radio call sign historically used by the British royal yacht HMY Britannia.
-
D.
golden house
The "golden house" refers to Nero's lavish Domus Aurea palace in ancient Rome, famed for its opulent decoration, innovative architecture, and extravagant use of gold.
-
E.
Gold
Gold is a 2016 American crime adventure film in which Matthew McConaughey stars as a prospector chasing a potentially fraudulent gold discovery in the Indonesian jungle.
- 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_69bd43d823288190952279faa0d1d066 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd6328387c81909a500e694a739e6e |
completed | March 20, 2026, 3:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdfaf9564c819094b9340570a7616b |
completed | March 21, 2026, 1:57 a.m. |
Created at: March 20, 2026, 1:15 p.m.