Triple
T5172720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vanessa |
E116721
|
entity |
| Predicate | hasVariantSpelling |
P457
|
FINISHED |
| Object |
Vannessa
Vannessa is a feminine given name, used as a variant spelling of Vanessa.
|
E499371
|
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: Vannessa | Statement: [Vanessa, hasVariantSpelling, Vannessa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vannessa Context triple: [Vanessa, hasVariantSpelling, Vannessa]
-
A.
Vanilla Dome
Vanilla Dome is an underground, lava-filled world in Super Mario World featuring maze-like caverns and challenging platforming stages.
-
B.
Malvids
Malvids are a major clade of flowering plants within the rosids that includes economically important families such as Brassicaceae (mustards) and Malvaceae (mallows).
-
C.
Vääna
Vääna is a village in northern Estonia known for its historic manor and coastal location near the capital, Tallinn.
-
D.
Vitasta
Vitasta is the ancient Sanskrit name for the Jhelum River, a historically significant river of the Kashmir region frequently mentioned in Vedic and classical Indian texts.
-
E.
Vanil Noir
Vanil Noir is a prominent mountain peak in the Swiss Prealps, known for its rugged limestone cliffs and panoramic views over the canton of Fribourg.
- 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: Vannessa Triple: [Vanessa, hasVariantSpelling, Vannessa]
Generated description
Vannessa is a feminine given name, used as a variant spelling of Vanessa.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Vannessa Target entity description: Vannessa is a feminine given name, used as a variant spelling of Vanessa.
-
A.
Vanilla Dome
Vanilla Dome is an underground, lava-filled world in Super Mario World featuring maze-like caverns and challenging platforming stages.
-
B.
Malvids
Malvids are a major clade of flowering plants within the rosids that includes economically important families such as Brassicaceae (mustards) and Malvaceae (mallows).
-
C.
Vääna
Vääna is a village in northern Estonia known for its historic manor and coastal location near the capital, Tallinn.
-
D.
Vitasta
Vitasta is the ancient Sanskrit name for the Jhelum River, a historically significant river of the Kashmir region frequently mentioned in Vedic and classical Indian texts.
-
E.
Vanil Noir
Vanil Noir is a prominent mountain peak in the Swiss Prealps, known for its rugged limestone cliffs and panoramic views over the canton of Fribourg.
- 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_69bd445ff97c81909a2615cc56235470 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd795252a481908634779f3f656574 |
completed | March 20, 2026, 4:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bed9471b4881909c8436853818a8a0 |
completed | March 21, 2026, 5:45 p.m. |
| NEDg | Description generation | batch_69bed9f3624c8190b9d22fa0594dd767 |
completed | March 21, 2026, 5:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69beda5d39b88190a7314f673de2719d |
completed | March 21, 2026, 5:50 p.m. |
Created at: March 20, 2026, 1:45 p.m.