Triple
T16986184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Miguel Department |
E412070
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Lolotique |
E914101
|
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: Lolotique | Statement: [San Miguel Department, contains, Lolotique]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lolotique Context triple: [San Miguel Department, contains, Lolotique]
-
A.
Lolovoli
Lolovoli is an indigenous language spoken on the island of Ambae in Vanuatu.
-
B.
Lolotiquillo
chosen
Lolotiquillo is a municipality located in the Morazán Department of northeastern El Salvador, known for its rural character and mountainous surroundings.
-
C.
Tillou
Tillou is a surname associated with individuals such as Emma Middleton Lynah Tillou, and is borne by various people of likely French or Francophone origin.
-
D.
Libolo
Libolo is a municipality located in Angola’s Cuanza Sul Province, known for its rural communities and agricultural activities.
-
E.
Lo Lo
"Lo Lo" is a popular Afrobeats song by Nigerian singer-songwriter Omah Lay, known for its smooth melodies and introspective lyrics.
- 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_69d886ca8f348190812768ea8d5055ce |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d27b58908190a643bcbd105b1849 |
completed | April 18, 2026, 6:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00dc1109a081908890bbd5958c76c2 |
completed | May 10, 2026, 7:27 p.m. |
Created at: April 10, 2026, 5:32 a.m.