Triple
T18745692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tau Sug |
E458398
|
entity |
| Predicate | traditionalVessel |
P22942
|
FINISHED |
| Object |
lepa-lepa
Lepa-lepa is a traditional wooden sailing canoe of the Tau Sug and other maritime peoples of the southern Philippines, used for fishing, transport, and coastal trade.
|
E1339771
|
NE FINISHED |
How this triple was built (4 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: lepa-lepa | Statement: [Tau Sug, traditionalVessel, lepa-lepa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: lepa-lepa Context triple: [Tau Sug, traditionalVessel, lepa-lepa]
-
A.
LEPA
LEPA is the ICAO airport code for Palma de Mallorca Airport, a major international airport in Spain’s Balearic Islands.
-
B.
Lep
Lep is the official three-letter IAU abbreviation for Lepus, a southern sky constellation located just below Orion.
-
C.
Lepar
Lepar is an island in Indonesia’s Bangka Belitung Islands province, known for its coastal landscapes and role in the region’s maritime and resource-based activities.
-
D.
Laprak
Laprak is a remote Gurung village in central Nepal’s Gorkha District, known for its traditional hillside settlements and severe damage during the 2015 earthquake.
-
E.
Lepel
Lepel is a small historic town in northeastern Belarus known for its lakes and location within the Vitebsk Region.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: lepa-lepa Triple: [Tau Sug, traditionalVessel, lepa-lepa]
Generated description
Lepa-lepa is a traditional wooden sailing canoe of the Tau Sug and other maritime peoples of the southern Philippines, used for fishing, transport, and coastal trade.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: lepa-lepa Target entity description: Lepa-lepa is a traditional wooden sailing canoe of the Tau Sug and other maritime peoples of the southern Philippines, used for fishing, transport, and coastal trade.
-
A.
LEPA
LEPA is the ICAO airport code for Palma de Mallorca Airport, a major international airport in Spain’s Balearic Islands.
-
B.
Lep
Lep is the official three-letter IAU abbreviation for Lepus, a southern sky constellation located just below Orion.
-
C.
Lepar
Lepar is an island in Indonesia’s Bangka Belitung Islands province, known for its coastal landscapes and role in the region’s maritime and resource-based activities.
-
D.
Laprak
Laprak is a remote Gurung village in central Nepal’s Gorkha District, known for its traditional hillside settlements and severe damage during the 2015 earthquake.
-
E.
Lepel
Lepel is a small historic town in northeastern Belarus known for its lakes and location within the Vitebsk Region.
- F. None of above. chosen
Provenance (5 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_69d8d394dc308190b6725073f5db324c |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e57692c380819091e8a919ab6c9ca9 |
completed | April 20, 2026, 12:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a053269162c8190bf4b780904026781 |
completed | May 14, 2026, 2:24 a.m. |
| NEDg | Description generation | batch_6a0532ce7c388190a8d6b2d83ec52354 |
completed | May 14, 2026, 2:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a053363f09c8190a7927345f1d027b3 |
completed | May 14, 2026, 2:28 a.m. |
Created at: April 10, 2026, 11:51 a.m.