Triple
T3646451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mao II |
E77312
|
entity |
| Predicate | setting |
P1957
|
FINISHED |
| Object | Beirut |
E4667
|
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: Beirut | Statement: [Mao II, setting, Beirut]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beirut Context triple: [Mao II, setting, Beirut]
-
A.
Beirut
chosen
Beirut is the capital and largest city of Lebanon, known as a historic cultural, commercial, and financial hub of the Eastern Mediterranean.
-
B.
Jounieh
Jounieh is a coastal city in Lebanon known for its seaside resorts, vibrant nightlife, and proximity to the historic pilgrimage site of Harissa.
-
C.
Tartus
Tartus is a major Syrian port city on the Mediterranean coast that hosts Russia’s only naval facility outside the former Soviet Union.
-
D.
Port of Beirut
The Port of Beirut is Lebanon’s principal maritime gateway and commercial hub on the Mediterranean Sea, historically central to the country’s trade and economy.
-
E.
Aleppo
Aleppo is an ancient and historically significant city in northern Syria, renowned for its rich cultural heritage, medieval architecture, and role as a major trading hub along the Silk Road.
- 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_69ad85de1b988190a45f8dbfebc806fc |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc3895198819090a17a8894e91d00 |
completed | March 8, 2026, 6:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b44f394f9c8190881edc18b544dbb7 |
completed | March 13, 2026, 5:54 p.m. |
Created at: March 8, 2026, 3:24 p.m.