Triple
T8144823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Le Trong Tan |
E190181
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Le |
E31362
|
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: Le | Statement: [Le Trong Tan, familyName, Le]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Le Context triple: [Le Trong Tan, familyName, Le]
-
A.
Le
chosen
Le is a common Vietnamese surname shared by many notable figures in the country’s history and culture.
-
B.
Lu
Lu is the traditional abbreviation and historical name used to refer to China’s Shandong province.
-
C.
Lo
Lo is a dialect of the Lo-Toga language spoken on the Torres Islands in northern Vanuatu.
-
D.
El
El is the common nickname for Philadelphia’s elevated Market–Frankford rapid transit line operated by SEPTA.
-
E.
El
El is the given name of El Anatsui, the renowned Ghanaian-Nigerian sculptor celebrated for his monumental metal wall hangings made from recycled materials.
- 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_69ca82be7ba8819087de0147e9292c83 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4445f1948190b8d319b60dd47f65 |
completed | March 31, 2026, 3:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc94b0fc0481909a21f42364a92158 |
completed | April 1, 2026, 3:44 a.m. |
Created at: March 30, 2026, 5:36 p.m.