Triple
T14670817
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aspire Tower |
E344506
|
entity |
| Predicate | architect |
P184
|
FINISHED |
| Object | Hadi Simaan |
E344506
|
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: Hadi Simaan | Statement: [Aspire Tower, architect, Hadi Simaan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hadi Simaan Context triple: [Aspire Tower, architect, Hadi Simaan]
-
A.
Hadi Simaan
chosen
Hadi Simaan is an architect best known for designing major landmark projects in the Middle East, including Doha’s Aspire Tower.
-
B.
Saad Haddad
Saad Haddad was a Lebanese militia leader and army officer who founded and commanded the Israeli-backed South Lebanon Army during the Lebanese Civil War.
-
C.
Talal Maddah
Talal Maddah was a pioneering Saudi Arabian singer and composer widely regarded as one of the most influential figures in modern Arabic music.
-
D.
Yasir Hamoudi
Yasir Hamoudi is a central character in the Canadian television sitcom "Little Mosque on the Prairie," known as the well-meaning but often beleaguered contractor and community leader.
-
E.
Hassan Aref
Hassan Aref was a prominent physicist and engineer known for his pioneering contributions to fluid dynamics, particularly in vortex dynamics and chaotic advection.
- 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_69d822e283fc8190a0e4c235cf880052 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb54ef2908190b189ced65eec434a |
completed | April 14, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdfb7c7df88190a4e551a12f6e8158 |
completed | May 8, 2026, 3:04 p.m. |
Created at: April 10, 2026, 1:27 a.m.