Triple
T10487016
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gabriela Mistral |
E247323
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Lagar
Lagar is a poetry collection by Chilean Nobel laureate Gabriela Mistral that reflects her mature, introspective, and often somber lyrical style.
|
E866954
|
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: Lagar | Statement: [Gabriela Mistral, notableWork, Lagar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lagar Context triple: [Gabriela Mistral, notableWork, Lagar]
-
A.
Lagada
Lagada is a small traditional village on the Greek island of Amorgos, known for its whitewashed houses, hillside setting, and views over the Aegean Sea.
-
B.
Laja
Laja is a small Chilean city in the Biobío Region, known for its riverside setting and proximity to the Biobío River.
-
C.
Luga
Luga is a small historic town in northwestern Russia known for its strategic location and role in regional transport and industry.
-
D.
Lagga
Lagga is a small locality in Sweden known as the birthplace of renowned sculptor Carl Milles.
-
E.
Larevat
Larevat is an Oceanic language spoken in Vanuatu, closely related to and geographically near the Uripiv-Wala-Rano-Atchin language cluster.
- 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: Lagar Triple: [Gabriela Mistral, notableWork, Lagar]
Generated description
Lagar is a poetry collection by Chilean Nobel laureate Gabriela Mistral that reflects her mature, introspective, and often somber lyrical style.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lagar Target entity description: Lagar is a poetry collection by Chilean Nobel laureate Gabriela Mistral that reflects her mature, introspective, and often somber lyrical style.
-
A.
Lagada
Lagada is a small traditional village on the Greek island of Amorgos, known for its whitewashed houses, hillside setting, and views over the Aegean Sea.
-
B.
Laja
Laja is a small Chilean city in the Biobío Region, known for its riverside setting and proximity to the Biobío River.
-
C.
Luga
Luga is a small historic town in northwestern Russia known for its strategic location and role in regional transport and industry.
-
D.
Lagga
Lagga is a small locality in Sweden known as the birthplace of renowned sculptor Carl Milles.
-
E.
Larevat
Larevat is an Oceanic language spoken in Vanuatu, closely related to and geographically near the Uripiv-Wala-Rano-Atchin language cluster.
- 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_69d381c309b88190af78aa681cf6a4c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5096a4d3481908e9c319f6cdce4f1 |
completed | April 7, 2026, 1:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d8dc8c73748190b97c78af6cf142d9 |
completed | April 10, 2026, 11:18 a.m. |
| NEDg | Description generation | batch_69d8e8c81bdc8190b6b6dfe00025b514 |
completed | April 10, 2026, 12:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d901e1ecf88190acd24a0e20462cb9 |
completed | April 10, 2026, 1:57 p.m. |
Created at: April 6, 2026, 12:23 p.m.