Triple
T2883552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gabi |
E59452
|
entity |
| Predicate | shortFormOf |
P43
|
FINISHED |
| Object |
Gabriela
Gabriela is a feminine given name of Spanish and Portuguese origin, serving as the counterpart to Gabriel.
|
E307088
|
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: Gabriela | Statement: [Gabi, shortFormOf, Gabriela]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gabriela Context triple: [Gabi, shortFormOf, Gabriela]
-
A.
Marita
Marita is a feminine given name commonly used as a diminutive or affectionate form of the name Marie in various European languages.
-
B.
Gabriella
Gabriella is a feminine given name of Italian origin, commonly used in many languages and often associated with the meaning "God is my strength."
-
C.
Carmelina
Carmelina is a lesser-known Broadway musical with music by Burton Lane and lyrics by Alan Jay Lerner, loosely based on the film "Buona Sera, Mrs. Campbell."
-
D.
Pilar
Pilar is a strong-willed, perceptive Spanish guerrilla fighter who plays a central role in Ernest Hemingway’s novel "For Whom the Bell Tolls."
-
E.
Pilar
Pilar is a riverside city in southwestern Paraguay known for its colonial architecture, river port activities, and proximity to the border with Argentina.
- 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: Gabriela Triple: [Gabi, shortFormOf, Gabriela]
Generated description
Gabriela is a feminine given name of Spanish and Portuguese origin, serving as the counterpart to Gabriel.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gabriela Target entity description: Gabriela is a feminine given name of Spanish and Portuguese origin, serving as the counterpart to Gabriel.
-
A.
Marita
Marita is a feminine given name commonly used as a diminutive or affectionate form of the name Marie in various European languages.
-
B.
Gabriella
chosen
Gabriella is a feminine given name of Italian origin, commonly used in many languages and often associated with the meaning "God is my strength."
-
C.
Carmelina
Carmelina is a lesser-known Broadway musical with music by Burton Lane and lyrics by Alan Jay Lerner, loosely based on the film "Buona Sera, Mrs. Campbell."
-
D.
Pilar
Pilar is a strong-willed, perceptive Spanish guerrilla fighter who plays a central role in Ernest Hemingway’s novel "For Whom the Bell Tolls."
-
E.
Pilar
Pilar is a riverside city in southwestern Paraguay known for its colonial architecture, river port activities, and proximity to the border with Argentina.
- F. None of above.
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_69ab4ac739188190a112f42a5a69c951 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abe02c238881908f7a349563c388bf |
completed | March 7, 2026, 8:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b0864dc2fc8190bfc946ae454611c6 |
completed | March 10, 2026, 8:59 p.m. |
| NEDg | Description generation | batch_69b0c36599788190b10bbd15d6c1fc6b |
completed | March 11, 2026, 1:20 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b0c3ca9f18819086b22d0bad79ff68 |
completed | March 11, 2026, 1:22 a.m. |
Created at: March 6, 2026, 10:03 p.m.